Andreas Krause

658 papers A* 186A 52B 9C 1Misc 8Journal 346Unranked 55

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Unified Density Operator View of Flow Control and Merging. CoRR Riccardo De Santi, Malte Franke, Ya-Ping Hsieh, Andreas Krause
2026	J	`jnl`	ActiveUltraFeedback: Efficient Preference Data Generation using Active Learning. CoRR Davit Melikidze, Marian Schneider, Jessica Lam, Martin Wertich, Ido Hakimi, Barna Pásztor, Andreas Krause
2026	J	`jnl`	Aligning Language Models from User Interactions. CoRR Thomas Kleine Buening, Jonas Hübotter, Barna Pásztor, Idan Shenfeld, Giorgia Ramponi, Andreas Krause
2026	J	`jnl`	Coding Agents with Environment Interaction: A Theoretical Perspective. CoRR Nicolas Menet, Michael Hersche, Andreas Krause, Abbas Rahimi
2026	J	`jnl`	Efficient Tail-Aware Generative Optimization via Flow Model Fine-Tuning. CoRR Zifan Wang, Riccardo De Santi, Xiaoyu Mo, Michael M. Zavlanos, Andreas Krause, Karl Henrik Johansson
2026	J	`jnl`	From Words To Rewards: Leveraging Natural Language For Reinforcement Learning. Trans. Mach. Learn. Res. Belen Martin-Urcelay, Andreas Krause, Giorgia Ramponi
2026	J	`jnl`	Latent Causal Diffusions for Single-Cell Perturbation Modeling. CoRR Lars Lorch, Jiaqi Zhang, Charlotte Bunne, Andreas Krause, Bernhard Schölkopf, Caroline Uhler
2026	J	`jnl`	Optimistic Online LQR via Intrinsic Rewards. CoRR Marcell Bartos, Bruce D. Lee, Lenart Treven, Andreas Krause, Florian Dörfler, Melanie N. Zeilinger
2026	J	`jnl`	Reinforcement Learning via Self-Distillation. CoRR Jonas Hübotter, Frederike Lübeck, Lejs Behric, Anton Baumann, Marco Bagatella, Daniel Marta, Ido Hakimi, Idan Shenfeld, Thomas Kleine Buening, Carlos Guestrin, Andreas Krause
2026	J	`jnl`	RewardUQ: A Unified Framework for Uncertainty-Aware Reward Models. CoRR Daniel Yang, Samuel Stante, Florian Redhardt, Lena Libon, Parnian Kassraie, Ido Hakimi, Barna Pásztor, Andreas Krause
2026	J	`jnl`	Robust-Sub-Gaussian Model Predictive Control for Safe Ultrasound-Image-Guided Robotic Spinal Surgery. IEEE Robotics Autom. Lett. Yunke Ao, Manish Prajapat, Yarden As, Yassine Taoudi-Benchekroun, Fabio Carrillo, Hooman Esfandiari, Benjamin F. Grewe, Andreas Krause, Philipp Fürnstahl
2026	J	`jnl`	Safe Exploration via Policy Priors. CoRR Manuel Wendl, Yarden As, Manish Prajapat, Anton Pollak, Stelian Coros, Andreas Krause
2026	J	`jnl`	Soft Forward-Backward Representations for Zero-shot Reinforcement Learning with General Utilities. CoRR Marco Bagatella, Thomas Rupf, Georg Martius, Andreas Krause
2026	J	`jnl`	Verifier-Constrained Flow Expansion for Discovery Beyond the Data. CoRR Riccardo De Santi, Kimon Protopapas, Ya-Ping Hsieh, Andreas Krause
2026	J	`jnl`	What Matters for Simulation to Online Reinforcement Learning on Real Robots. CoRR Yarden As, Dhruva Tirumala, René Zurbrügg, Chenhao Li, Stelian Coros, Andreas Krause, Markus Wulfmeier
2025	A*	`conf`	ActSafe: Active Exploration with Safety Constraints for Reinforcement Learning. ICLR Yarden As, Bhavya Sukhija, Lenart Treven, Carmelo Sferrazza, Stelian Coros, Andreas Krause
2025	A*	`conf`	Active Fine-Tuning of Multi-Task Policies. ICML Marco Bagatella, Jonas Hübotter, Georg Martius, Andreas Krause
2025	J	`jnl`	Adaptable Cardiovascular Disease Risk Prediction from Heterogeneous Data using Large Language Models. CoRR Frederike Lübeck, Jonas Wildberger, Frederik Träuble, Maximilian Mordig, Sergios Gatidis, Andreas Krause, Bernhard Schölkopf
2025	A	`conf`	All models are wrong, some are useful: Model Selection with Limited Labels. AISTATS Patrik Okanovic, Andreas Kirsch, Jannes Kasper, Torsten Hoefler, Andreas Krause, Nezihe Merve Gürel
2025	A*	`conf`	Composing Unbalanced Flows for Flexible Docking and Relaxation. ICLR Gabriele Corso, Vignesh Ram Somnath, Noah Getz, Regina Barzilay, Tommi S. Jaakkola, Andreas Krause
2025	J	`jnl`	Confidence Estimation via Sequential Likelihood Mixing. CoRR Johannes Kirschner, Andreas Krause, Michele Meziu, Mojmir Mutny
2025	J	`jnl`	DISCOVER: Automated Curricula for Sparse-Reward Reinforcement Learning. CoRR Leander Diaz-Bone, Marco Bagatella, Jonas Hübotter, Andreas Krause
2025	J	`jnl`	Directed Exploration in Reinforcement Learning from Linear Temporal Logic. Trans. Mach. Learn. Res. Marco Bagatella, Andreas Krause, Georg Martius
2025	J	`jnl`	Distributed Risk-Sensitive Safety Filters for Uncertain Discrete-Time Systems. CoRR Armin Lederer, Erfaun Noorani, Andreas Krause
2025	J	`jnl`	Distributed Risk-Sensitive Safety Filters for Uncertain Discrete-Time Systems. IEEE Control. Syst. Lett. Armin Lederer, Erfaun Noorani, Andreas Krause
2025	J	`jnl`	Efficient Personalization of Generative Models via Optimal Experimental Design. CoRR Guy Schacht, Ziyad Sheebaelhamd, Riccardo De Santi, Mojmír Mutný, Andreas Krause
2025	A*	`conf`	Efficiently Learning at Test-Time: Active Fine-Tuning of LLMs. ICLR Jonas Hübotter, Sascha Bongni, Ido Hakimi, Andreas Krause
2025	J	`jnl`	Feature-Based vs. GAN-Based Learning from Demonstrations: When and Why. CoRR Chenhao Li, Marco Hutter, Andreas Krause
2025	J	`jnl`	Finite-Sample-Based Reachability for Safe Control with Gaussian Process Dynamics. CoRR Manish Prajapat, Johannes Köhler, Amon Lahr, Andreas Krause, Melanie N. Zeilinger
2025	J	`jnl`	Flow Density Control: Generative Optimization Beyond Entropy-Regularized Fine-Tuning. CoRR Riccardo De Santi, Marin Vlastelica, Ya-Ping Hsieh, Zebang Shen, Niao He, Andreas Krause
2025	A*	`conf`	Generative Intervention Models for Causal Perturbation Modeling. ICML Nora Schneider, Lars Lorch, Niki Kilbertus, Bernhard Schölkopf, Andreas Krause
2025	J	`jnl`	International AI Safety Report. CoRR Yoshua Bengio, Sören Mindermann, Daniel Privitera, Tamay Besiroglu, Rishi Bommasani, Stephen Casper, Yejin Choi, Philip Fox, Ben Garfinkel, Danielle Goldfarb, Hoda Heidari, Anson Ho, Sayash Kapoor, Leila Khalatbari, Shayne Longpre, Sam Manning, Vasilios Mavroudis, Mantas Mazeika, Julian Michael, Jessica Newman, Kwan Yee Ng, Chinasa T. Okolo, Inioluwa Deborah Raji, Girish Sastry, Elizabeth Seger, Theodora Skeadas, Tobin South, Emma Strubell, Florian Tramèr, Lucia Velasco, Nicole Wheeler, Daron Acemoglu, Olubayo Adekanmbi, David Dalrymple, Thomas G. Dietterich, Edward W. Felten, Pascale Fung, Pierre-Olivier Gourinchas, Fredrik Heintz, Geoffrey E. Hinton, Nick R. Jennings, Andreas Krause, Susan Leavy, Percy Liang, Teresa Ludermir, Vidushi Marda, Helen Margetts, John A. McDermid, Jane Munga, Arvind Narayanan, Alondra Nelson, Clara Neppel, Alice Oh, Gopal Ramchurn, Stuart Russell, Marietje Schaake, Bernhard Schölkopf, Dawn Song, Alvaro Soto, Lee Tiedrich, Gaël Varoquaux, Andrew Yao, Ya-Qin Zhang, Fahad Albalawi, Marwan Alserkal, Olubunmi Ajala, Guillaume Avrin, Christian Busch, André Carlos Ponce de Leon Ferreira de Carvalho, Bronwyn Fox, Amandeep Singh Gill, Ahmet Halit Hatip, Juha Heikkilä, Gill Jolly, Ziv Katzir, Hiroaki Kitano, Antonio Krüger, Chris Johnson, Saif M. Khan, Kyoung Mu Lee, Dominic Vincent Ligot, Oleksii Molchanovskyi, Andrea Monti, Nusu Mwamanzi, Mona Nemer, Nuria Oliver, José Ramón López Portillo, Balaraman Ravindran, Raquel Pezoa Rivera, Hammam Riza, Crystal Rugege, Ciarán Seoighe, Jerry Sheehan, Haroon Sheikh, Denise Wong, Yi Zeng
2025	A	`conf`	LITE: Efficiently Estimating Gaussian Probability of Maximality. AISTATS Nicolas Menet, Jonas Hübotter, Parnian Kassraie, Andreas Krause
2025	J	`jnl`	LITE: Efficiently Estimating Gaussian Probability of Maximality. CoRR Nicolas Menet, Jonas Hübotter, Parnian Kassraie, Andreas Krause
2025	A*	`conf`	Learning Safety Constraints for Large Language Models. ICML Xin Chen, Yarden As, Andreas Krause
2025	J	`jnl`	Learning Safety Constraints for Large Language Models. CoRR Xin Chen, Yarden As, Andreas Krause
2025	J	`jnl`	Learning Soft Robotic Dynamics with Active Exploration. CoRR Hehui Zheng, Bhavya Sukhija, Chenhao Li, Klemens Iten, Andreas Krause, Robert K. Katzschmann
2025	J	`jnl`	Learning on the Job: Test-Time Curricula for Targeted Reinforcement Learning. CoRR Jonas Hübotter, Leander Diaz-Bone, Ido Hakimi, Andreas Krause, Moritz Hardt
2025	J	`jnl`	Local Mixtures of Experts: Essentially Free Test-Time Training via Model Merging. CoRR Ryo Bertolissi, Jonas Hübotter, Ido Hakimi, Andreas Krause
2025	A*	`conf`	MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization. ICLR Bhavya Sukhija, Stelian Coros, Andreas Krause, Pieter Abbeel, Carmelo Sferrazza
2025	J	`jnl`	Maximizing Prefix-Confidence at Test-Time Efficiently Improves Mathematical Reasoning. CoRR Matthias Otth, Jonas Hübotter, Ido Hakimi, Andreas Krause
2025	J	`jnl`	NIL: No-data Imitation Learning by Leveraging Pre-trained Video Diffusion Models. CoRR Mert Albaba, Chenhao Li, Markos Diomataris, Omid Taheri, Andreas Krause, Michael Julian Black
2025	J	`jnl`	Offline Robotic World Model: Learning Robotic Policies without a Physics Simulator. CoRR Chenhao Li, Andreas Krause, Marco Hutter
2025	A*	`conf`	Optimistic Games for Combinatorial Bayesian Optimization with Application to Protein Design. ICLR Melis Ilayda Bal, Pier Giuseppe Sessa, Mojmir Mutny, Andreas Krause
2025	J	`jnl`	Optimistic Task Inference for Behavior Foundation Models. CoRR Thomas Rupf, Marco Bagatella, Marin Vlastelica, Andreas Krause
2025	J	`jnl`	PAC-Bayesian Optimal Control with Stability and Generalization Guarantees. CoRR Mahrokh Ghoddousi Boroujeni, Clara Lucía Galimberti, Andreas Krause, Giancarlo Ferrari-Trecate
2025	J	`jnl`	Performance-Driven Constrained Optimal Auto-Tuner for MPC. IEEE Robotics Autom. Lett. Albert Gassol Puigjaner, Manish Prajapat, Andrea Carron, Andreas Krause, Melanie N. Zeilinger
2025	J	`jnl`	Performance-driven Constrained Optimal Auto-Tuner for MPC. CoRR Albert Gassol Puigjaner, Manish Prajapat, Andrea Carron, Andreas Krause, Melanie N. Zeilinger
2025	J	`jnl`	Personalized Federated Learning of Probabilistic Models: A PAC-Bayesian Approach. Trans. Mach. Learn. Res. Mahrokh Ghoddousi Boroujeni, Andreas Krause, Giancarlo Ferrari-Trecate
2025	J	`jnl`	Probabilistic Artificial Intelligence. CoRR Andreas Krause, Jonas Hübotter
2025	A*	`conf`	Provable Maximum Entropy Manifold Exploration via Diffusion Models. ICML Riccardo De Santi, Marin Vlastelica, Ya-Ping Hsieh, Zebang Shen, Niao He, Andreas Krause
2025	J	`jnl`	Provable Maximum Entropy Manifold Exploration via Diffusion Models. CoRR Riccardo De Santi, Marin Vlastelica, Ya-Ping Hsieh, Zebang Shen, Niao He, Andreas Krause
2025	A*	`conf`	Residual Deep Gaussian Processes on Manifolds. ICLR Kacper Wyrwal, Andreas Krause, Viacheslav Borovitskiy
2025	J	`jnl`	Ride-Sourcing Vehicle Rebalancing with Service Accessibility Guarantees via Constrained Mean-Field Reinforcement Learning. CoRR Matej Jusup, Kenan Zhang, Zhiyuan Hu, Barna Pásztor, Andreas Krause, Francesco Corman
2025	J	`jnl`	Robotic World Model: A Neural Network Simulator for Robust Policy Optimization in Robotics. CoRR Chenhao Li, Andreas Krause, Marco Hutter
2025	J	`jnl`	Robust-Sub-Gaussian Model Predictive Control for Safe Ultrasound-Image-Guided Robotic Spinal Surgery. CoRR Yunke Ao, Manish Prajapat, Yarden As, Yassine Taoudi-Benchekroun, Fabio Carrillo, Hooman Esfandiari, Benjamin F. Grewe, Andreas Krause, Philipp Fürnstahl
2025	J	`jnl`	SOMBRL: Scalable and Optimistic Model-Based RL. CoRR Bhavya Sukhija, Lenart Treven, Carmelo Sferrazza, Florian Dörfler, Pieter Abbeel, Andreas Krause
2025	J	`jnl`	SPiDR: A Simple Approach for Zero-Shot Safety in Sim-to-Real Transfer. CoRR Yarden As, Chengrui Qu, Benjamin Unger, Dongho Kang, Max van der Hart, Laixi Shi, Stelian Coros, Adam Wierman, Andreas Krause
2025	J	`jnl`	Safe Guaranteed Dynamics Exploration with Probabilistic Models. CoRR Manish Prajapat, Johannes Köhler, Melanie N. Zeilinger, Andreas Krause
2025	J	`jnl`	Safe Guaranteed Exploration for Nonlinear Systems. IEEE Trans. Autom. Control. Manish Prajapat, Johannes Köhler, Matteo Turchetta, Andreas Krause, Melanie N. Zeilinger
2025	J	`jnl`	SafeRPlan: Safe deep reinforcement learning for intraoperative planning of pedicle screw placement. Medical Image Anal. Yunke Ao, Hooman Esfandiari, Fabio Carrillo, Christoph J. Laux, Yarden As, Ruixuan Li, Kaat Van Assche, Ayoob Davoodi, Nicola Alessandro Cavalcanti, Mazda Farshad, Benjamin F. Grewe, Emmanuel B. Vander Poorten, Andreas Krause, Philipp Fürnstahl
2025	J	`jnl`	Sample-efficient and Scalable Exploration in Continuous-Time RL. CoRR Klemens Iten, Lenart Treven, Bhavya Sukhija, Florian Dörfler, Andreas Krause
2025	J	`jnl`	Simulation Priors for Data-Efficient Deep Learning. CoRR Lenart Treven, Bhavya Sukhija, Jonas Rothfuss, Stelian Coros, Florian Dörfler, Andreas Krause
2025	J	`jnl`	SonoGym: High Performance Simulation for Challenging Surgical Tasks with Robotic Ultrasound. CoRR Yunke Ao, Masoud Moghani, Mayank Mittal, Manish Prajapat, Luohong Wu, Frédéric H. Giraud, Fabio Carrillo, Andreas Krause, Philipp Fürnstahl
2025	J	`jnl`	Specialization after Generalization: Towards Understanding Test-Time Training in Foundation Models. CoRR Jonas Hübotter, Patrik Wolf, Alexander Shevchenko, Dennis Jüni, Andreas Krause, Gil Kur
2025	J	`jnl`	Stackelberg Learning from Human Feedback: Preference Optimization as a Sequential Game. CoRR Barna Pásztor, Thomas Kleine Buening, Andreas Krause
2025	A*	`conf`	Standardizing Structural Causal Models. ICLR Weronika Ormaniec, Scott Sussex, Lars Lorch, Bernhard Schölkopf, Andreas Krause
2025	J	`jnl`	Stochastic Model Predictive Control for Sub-Gaussian Noise. CoRR Yunke Ao, Johannes Köhler, Manish Prajapat, Yarden As, Melanie Nicole Zeilinger, Philipp Fürnstahl, Andreas Krause
2025	J	`jnl`	TARC: Time-Adaptive Robotic Control. CoRR Arnav Sukhija, Lenart Treven, Jin Cheng, Florian Dörfler, Stelian Coros, Andreas Krause
2025	J	`jnl`	Test-time Offline Reinforcement Learning on Goal-related Experience. CoRR Marco Bagatella, Mert Albaba, Jonas Hübotter, Georg Martius, Andreas Krause
2025	J	`jnl`	Thompson Sampling via Fine-Tuning of LLMs. CoRR Nicolas Menet, Aleksandar Terzic, Michael Hersche, Andreas Krause, Abbas Rahimi
2025	J	`jnl`	Toward Task Generalization via Memory Augmentation in Meta-Reinforcement Learning. CoRR Kaixi Bao, Chenhao Li, Yarden As, Andreas Krause, Marco Hutter
2024	J	`jnl`	3DReact: Geometric Deep Learning for Chemical Reactions. J. Chem. Inf. Model. Puck van Gerwen, Ksenia R. Briling, Charlotte Bunne, Vignesh Ram Somnath, Rubén Laplaza, Andreas Krause, Clémence Corminboeuf
2024	—	`conf`	A PAC-Bayesian Framework for Optimal Control with Stability Guarantees. CDC Mahrokh Ghoddousi Boroujeni, Clara Lucía Galimberti, Andreas Krause, Giancarlo Ferrari-Trecate
2024	J	`jnl`	A PAC-Bayesian Framework for Optimal Control with Stability Guarantees. CoRR Mahrokh Ghoddousi Boroujeni, Clara Lucía Galimberti, Andreas Krause, Giancarlo Ferrari-Trecate
2024	J	`jnl`	ActSafe: Active Exploration with Safety Constraints for Reinforcement Learning. CoRR Yarden As, Bhavya Sukhija, Lenart Treven, Carmelo Sferrazza, Stelian Coros, Andreas Krause
2024	J	`jnl`	Active Few-Shot Fine-Tuning. CoRR Jonas Hübotter, Bhavya Sukhija, Lenart Treven, Yarden As, Andreas Krause
2024	J	`jnl`	Active Fine-Tuning of Generalist Policies. CoRR Marco Bagatella, Jonas Hübotter, Georg Martius, Andreas Krause
2024	A*	`conf`	Adversarial Causal Bayesian Optimization. ICLR Scott Sussex, Pier Giuseppe Sessa, Anastasia Makarova, Andreas Krause
2024	J	`jnl`	All models are wrong, some are useful: Model Selection with Limited Labels. CoRR Patrik Okanovic, Andreas Kirsch, Jannes Kasper, Torsten Hoefler, Andreas Krause, Nezihe Merve Gürel
2024	J	`jnl`	Amortized SHAP values via sparse Fourier function approximation. CoRR Ali Gorji, Andisheh Amrollahi, Andreas Krause
2024	A*	`conf`	Bandits with Preference Feedback: A Stackelberg Game Perspective. NeurIPS Barna Pásztor, Parnian Kassraie, Andreas Krause
2024	J	`jnl`	Bandits with Preference Feedback: A Stackelberg Game Perspective. CoRR Barna Pásztor, Parnian Kassraie, Andreas Krause
2024	J	`jnl`	Breeding Programs Optimization with Reinforcement Learning. CoRR Omar G. Younis, Luca Corinzia, Ioannis N. Athanasiadis, Andreas Krause, Joachim M. Buhmann, Matteo Turchetta
2024	A	`conf`	Bridging the Sim-to-Real Gap with Bayesian Inference. IROS Jonas Rothfuss, Bhavya Sukhija, Lenart Treven, Florian Dörfler, Stelian Coros, Andreas Krause
2024	J	`jnl`	Bridging the Sim-to-Real Gap with Bayesian Inference. CoRR Jonas Rothfuss, Bhavya Sukhija, Lenart Treven, Florian Dörfler, Stelian Coros, Andreas Krause
2024	A	`conf`	Causal Modeling with Stationary Diffusions. AISTATS Lars Lorch, Andreas Krause, Bernhard Schölkopf
2024	A*	`conf`	Contextual Bilevel Reinforcement Learning for Incentive Alignment. NeurIPS Vinzenz Thoma, Barna Pásztor, Andreas Krause, Giorgia Ramponi, Yifan Hu
2024	J	`jnl`	Data Summarization via Bilevel Optimization. J. Mach. Learn. Res. Zalán Borsos, Mojmír Mutný, Marco Tagliasacchi, Andreas Krause
2024	J	`jnl`	Data-Efficient Task Generalization via Probabilistic Model-Based Meta Reinforcement Learning. IEEE Robotics Autom. Lett. Arjun Bhardwaj, Jonas Rothfuss, Bhavya Sukhija, Yarden As, Marco Hutter, Stelian Coros, Andreas Krause
2024	J	`jnl`	Directed Exploration in Reinforcement Learning from Linear Temporal Logic. CoRR Marco Bagatella, Andreas Krause, Georg Martius
2024	A	`conf`	Distributionally Robust Model-based Reinforcement Learning with Large State Spaces. AISTATS Shyam Sundhar Ramesh, Pier Giuseppe Sessa, Yifan Hu, Andreas Krause, Ilija Bogunovic
2024	J	`jnl`	Efficiently Learning at Test-Time: Active Fine-Tuning of LLMs. CoRR Jonas Hübotter, Sascha Bongni, Ido Hakimi, Andreas Krause
2024	J	`jnl`	Generative Intervention Models for Causal Perturbation Modeling. CoRR Nora Schneider, Lars Lorch, Niki Kilbertus, Bernhard Schölkopf, Andreas Krause
2024	A*	`conf`	Geometric Active Exploration in Markov Decision Processes: the Benefit of Abstraction. ICML Riccardo De Santi, Federico Arangath Joseph, Noah Liniger, Mirco Mutti, Andreas Krause
2024	J	`jnl`	Geometric Active Exploration in Markov Decision Processes: the Benefit of Abstraction. CoRR Riccardo De Santi, Federico Arangath Joseph, Noah Liniger, Mirco Mutti, Andreas Krause
2024	A*	`conf`	Global Reinforcement Learning : Beyond Linear and Convex Rewards via Submodular Semi-gradient Methods. ICML Riccardo De Santi, Manish Prajapat, Andreas Krause
2024	J	`jnl`	Global Reinforcement Learning: Beyond Linear and Convex Rewards via Submodular Semi-gradient Methods. CoRR Riccardo De Santi, Manish Prajapat, Andreas Krause
2024	J	`jnl`	Information-based Transductive Active Learning. CoRR Jonas Hübotter, Bhavya Sukhija, Lenart Treven, Yarden As, Andreas Krause
2024	J	`jnl`	International Scientific Report on the Safety of Advanced AI (Interim Report). CoRR Yoshua Bengio, Sören Mindermann, Daniel Privitera, Tamay Besiroglu, Rishi Bommasani, Stephen Casper, Yejin Choi, Danielle Goldfarb, Hoda Heidari, Leila Khalatbari, Shayne Longpre, Vasilios Mavroudis, Mantas Mazeika, Kwan Yee Ng, Chinasa T. Okolo, Inioluwa Deborah Raji, Theodora Skeadas, Florian Tramèr, Bayo Adekanmbi, Paul F. Christiano, David Dalrymple, Thomas G. Dietterich, Edward W. Felten, Pascale Fung, Pierre-Olivier Gourinchas, Nick R. Jennings, Andreas Krause, Percy Liang, Teresa Ludermir, Vidushi Marda, Helen Margetts, John A. McDermid, Arvind Narayanan, Alondra Nelson, Alice Oh, Gopal Ramchurn, Stuart Russell, Marietje Schaake, Dawn Song, Alvaro Soto, Lee Tiedrich, Gaël Varoquaux, Andrew Yao, Ya-Qin Zhang
2024	A	`conf`	Intrinsic Gaussian Vector Fields on Manifolds. AISTATS Daniel Robert-Nicoud, Andreas Krause, Viacheslav Borovitskiy
2024	A	`conf`	Learning Safety Constraints from Demonstrations with Unknown Rewards. AISTATS David Lindner, Xin Chen, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause
2024	J	`jnl`	Log Barriers for Safe Black-box Optimization with Application to Safe Reinforcement Learning. J. Mach. Learn. Res. Ilnura Usmanova, Yarden As, Maryam Kamgarpour, Andreas Krause
2024	J	`jnl`	MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization. CoRR Bhavya Sukhija, Stelian Coros, Andreas Krause, Pieter Abbeel, Carmelo Sferrazza
2024	A*	`conf`	Model-Based RL for Mean-Field Games is not Statistically Harder than Single-Agent RL. ICML Jiawei Huang, Niao He, Andreas Krause
2024	J	`jnl`	Model-Based RL for Mean-Field Games is not Statistically Harder than Single-Agent RL. CoRR Jiawei Huang, Niao He, Andreas Krause
2024	A*	`conf`	NeoRL: Efficient Exploration for Nonepisodic RL. NeurIPS Bhavya Sukhija, Lenart Treven, Florian Dörfler, Stelian Coros, Andreas Krause
2024	J	`jnl`	NeoRL: Efficient Exploration for Nonepisodic RL. CoRR Bhavya Sukhija, Lenart Treven, Florian Dörfler, Stelian Coros, Andreas Krause
2024	J	`jnl`	Optimistic Games for Combinatorial Bayesian Optimization with Application to Protein Design. CoRR Melis Ilayda Bal, Pier Giuseppe Sessa, Mojmir Mutny, Andreas Krause
2024	J	`jnl`	Personalized Federated Learning of Probabilistic Models: A PAC-Bayesian Approach. CoRR Mahrokh Ghoddousi Boroujeni, Andreas Krause, Giancarlo Ferrari-Trecate
2024	A	`conf`	Provably Learning Nash Policies in Constrained Markov Potential Games. AAMAS Pragnya Alatur, Giorgia Ramponi, Niao He, Andreas Krause
2024	J	`jnl`	Residual Deep Gaussian Processes on Manifolds. CoRR Kacper Wyrwal, Andreas Krause, Viacheslav Borovitskiy
2024	J	`jnl`	Safe Exploration Using Bayesian World Models and Log-Barrier Optimization. CoRR Yarden As, Bhavya Sukhija, Andreas Krause
2024	J	`jnl`	Safe Guaranteed Exploration for Non-linear Systems. CoRR Manish Prajapat, Johannes Köhler, Matteo Turchetta, Andreas Krause, Melanie N. Zeilinger
2024	A	`conf`	Safe Model-Based Multi-Agent Mean-Field Reinforcement Learning. AAMAS Matej Jusup, Barna Pásztor, Tadeusz Janik, Kenan Zhang, Francesco Corman, Andreas Krause, Ilija Bogunovic
2024	A	`conf`	Sinkhorn Flow as Mirror Flow: A Continuous-Time Framework for Generalizing the Sinkhorn Algorithm. AISTATS Mohammad Reza Karimi, Ya-Ping Hsieh, Andreas Krause
2024	J	`jnl`	Standardizing Structural Causal Models. CoRR Weronika Ormaniec, Scott Sussex, Lars Lorch, Bernhard Schölkopf, Andreas Krause
2024	J	`jnl`	Stochastic Bilevel Optimization with Lower-Level Contextual Markov Decision Processes. CoRR Vinzenz Thoma, Barna Pásztor, Andreas Krause, Giorgia Ramponi, Yifan Hu
2024	A*	`conf`	Submodular Reinforcement Learning. ICLR Manish Prajapat, Mojmir Mutny, Melanie N. Zeilinger, Andreas Krause
2024	—	`conf`	Towards safe and tractable Gaussian process-based MPC: Efficient sampling within a sequential quadratic programming framework. CDC Manish Prajapat, Amon Lahr, Johannes Köhler, Andreas Krause, Melanie N. Zeilinger
2024	J	`jnl`	Towards safe and tractable Gaussian process-based MPC: Efficient sampling within a sequential quadratic programming framework. CoRR Manish Prajapat, Amon Lahr, Johannes Köhler, Andreas Krause, Melanie N. Zeilinger
2024	A*	`conf`	Transductive Active Learning: Theory and Applications. NeurIPS Jonas Hübotter, Bhavya Sukhija, Lenart Treven, Yarden As, Andreas Krause
2024	A*	`conf`	Transition Constrained Bayesian Optimization via Markov Decision Processes. NeurIPS Jose Pablo Folch, Calvin Tsay, Robert M. Lee, Behrang Shafei, Weronika Ormaniec, Andreas Krause, Mark van der Wilk, Ruth Misener, Mojmir Mutny
2024	J	`jnl`	Transition Constrained Bayesian Optimization via Markov Decision Processes. CoRR Jose Pablo Folch, Calvin Tsay, Robert M. Lee, Behrang Shafei, Weronika Ormaniec, Andreas Krause, Mark van der Wilk, Ruth Misener, Mojmír Mutný
2024	A*	`conf`	When to Sense and Control? A Time-adaptive Approach for Continuous-Time RL. NeurIPS Lenart Treven, Bhavya Sukhija, Yarden As, Florian Dörfler, Andreas Krause
2024	J	`jnl`	When to Sense and Control? A Time-adaptive Approach for Continuous-Time RL. CoRR Lenart Treven, Bhavya Sukhija, Yarden As, Florian Dörfler, Andreas Krause
2023	A*	`conf`	A Dynamical System View of Langevin-Based Non-Convex Sampling. NeurIPS Mohammad Reza Karimi Jaghargh, Ya-Ping Hsieh, Andreas Krause
2023	J	`jnl`	A Scalable Walsh-Hadamard Regularizer to Overcome the Low-degree Spectral Bias of Neural Networks. CoRR Ali Gorji, Andisheh Amrollahi, Andreas Krause
2023	A	`conf`	A scalable Walsh-Hadamard regularizer to overcome the low-degree spectral bias of neural networks. UAI Ali Gorji, Andisheh Amrollahi, Andreas Krause
2023	A	`conf`	Active Exploration via Experiment Design in Markov Chains. AISTATS Mojmir Mutny, Tadeusz Janik, Andreas Krause
2023	A	`conf`	Aligned Diffusion Schrödinger Bridges. UAI Vignesh Ram Somnath, Matteo Pariset, Ya-Ping Hsieh, María Rodríguez Martínez, Andreas Krause, Charlotte Bunne
2023	J	`jnl`	Aligned Diffusion Schrödinger Bridges. CoRR Vignesh Ram Somnath, Matteo Pariset, Ya-Ping Hsieh, María Rodríguez Martínez, Andreas Krause, Charlotte Bunne
2023	A*	`conf`	Anytime Model Selection in Linear Bandits. NeurIPS Parnian Kassraie, Nicolas Emmenegger, Andreas Krause, Aldo Pacchiano
2023	J	`jnl`	Anytime Model Selection in Linear Bandits. CoRR Parnian Kassraie, Aldo Pacchiano, Nicolas Emmenegger, Andreas Krause
2023	A	`conf`	BaCaDI: Bayesian Causal Discovery with Unknown Interventions. AISTATS Alexander Hägele, Jonas Rothfuss, Lars Lorch, Vignesh Ram Somnath, Bernhard Schölkopf, Andreas Krause
2023	J	`jnl`	Bayesian optimization with safety constraints: safe and automatic parameter tuning in robotics. Mach. Learn. Felix Berkenkamp, Andreas Krause, Angela P. Schoellig
2023	J	`jnl`	Causal Modeling with Stationary Diffusions. CoRR Lars Lorch, Andreas Krause, Bernhard Schölkopf
2023	J	`jnl`	ChromaX: a fast and scalable breeding program simulator. Bioinform. Omar G. Younis, Matteo Turchetta, Daniel Ariza Suarez, Steven Yates, Bruno Studer, Ioannis N. Athanasiadis, Andreas Krause, Joachim M. Buhmann, Luca Corinzia
2023	A*	`conf`	Contextual Stochastic Bilevel Optimization. NeurIPS Yifan Hu, Jie Wang, Yao Xie, Andreas Krause, Daniel Kuhn
2023	J	`jnl`	Contextual Stochastic Bilevel Optimization. CoRR Yifan Hu, Jie Wang, Yao Xie, Andreas Krause, Daniel Kuhn
2023	J	`jnl`	Data-Efficient Task Generalization via Probabilistic Model-based Meta Reinforcement Learning. CoRR Arjun Bhardwaj, Jonas Rothfuss, Bhavya Sukhija, Yarden As, Marco Hutter, Stelian Coros, Andreas Krause
2023	J	`jnl`	Distributionally Robust Model-based Reinforcement Learning with Large State Spaces. CoRR Shyam Sundhar Ramesh, Pier Giuseppe Sessa, Yifan Hu, Andreas Krause, Ilija Bogunovic
2023	J	`jnl`	DockGame: Cooperative Games for Multimeric Rigid Protein Docking. CoRR Vignesh Ram Somnath, Pier Giuseppe Sessa, María Rodríguez Martínez, Andreas Krause
2023	A*	`conf`	Efficient Exploration in Continuous-time Model-based Reinforcement Learning. NeurIPS Lenart Treven, Jonas Hübotter, Bhavya Sukhija, Florian Dörfler, Andreas Krause
2023	J	`jnl`	Efficient Exploration in Continuous-time Model-based Reinforcement Learning. CoRR Lenart Treven, Jonas Hübotter, Bhavya Sukhija, Florian Dörfler, Andreas Krause
2023	J	`jnl`	Efficient Model-Based Multi-Agent Mean-Field Reinforcement Learning. Trans. Mach. Learn. Res. Barna Pásztor, Andreas Krause, Ilija Bogunovic
2023	J	`jnl`	EquiReact: An equivariant neural network for chemical reactions. CoRR Puck van Gerwen, Ksenia R. Briling, Charlotte Bunne, Vignesh Ram Somnath, Rubén Laplaza, Andreas Krause, Clémence Corminboeuf
2023	J	`jnl`	GoSafeOpt: Scalable safe exploration for global optimization of dynamical systems. Artif. Intell. Bhavya Sukhija, Matteo Turchetta, David Lindner, Andreas Krause, Sebastian Trimpe, Dominik Baumann
2023	A*	`conf`	Gradient-Based Trajectory Optimization With Learned Dynamics. ICRA Bhavya Sukhija, Nathanael Köhler, Miguel Zamora, Simon Zimmermann, Sebastian Curi, Andreas Krause, Stelian Coros
2023	J	`jnl`	Hallucinated Adversarial Control for Conservative Offline Policy Evaluation. CoRR Jonas Rothfuss, Bhavya Sukhija, Tobias Birchler, Parnian Kassraie, Andreas Krause
2023	A	`conf`	Hallucinated adversarial control for conservative offline policy evaluation. UAI Jonas Rothfuss, Bhavya Sukhija, Tobias Birchler, Parnian Kassraie, Andreas Krause
2023	A*	`conf`	Implicit Manifold Gaussian Process Regression. NeurIPS Bernardo Fichera, Slava Borovitskiy, Andreas Krause, Aude Gemma Billard
2023	J	`jnl`	Implicit Manifold Gaussian Process Regression. CoRR Bernardo Fichera, Viacheslav Borovitskiy, Andreas Krause, Aude Billard
2023	J	`jnl`	Incentive-Compatible Forecasting Competitions. Manag. Sci. Jens Witkowski, Rupert Freeman, Jennifer Wortman Vaughan, David M. Pennock, Andreas Krause
2023	J	`jnl`	Instance-Dependent Generalization Bounds via Optimal Transport. J. Mach. Learn. Res. Songyan Hou, Parnian Kassraie, Anastasis Kratsios, Andreas Krause, Jonas Rothfuss
2023	A*	`ed.`	International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA. ICML Andreas Krause, Emma Brunskill, Kyunghyun Cho, Barbara Engelhardt, Sivan Sabato, Jonathan Scarlett
2023	J	`jnl`	Intrinsic Gaussian Vector Fields on Manifolds. CoRR Daniel Robert-Nicoud, Andreas Krause, Viacheslav Borovitskiy
2023	A	`conf`	Isotropic Gaussian Processes on Finite Spaces of Graphs. AISTATS Viacheslav Borovitskiy, Mohammad Reza Karimi, Vignesh Ram Somnath, Andreas Krause
2023	J	`jnl`	Learning Safety Constraints from Demonstrations with Unknown Rewards. CoRR David Lindner, Xin Chen, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause
2023	A*	`conf`	Learning To Dive In Branch And Bound. NeurIPS Max B. Paulus, Andreas Krause
2023	J	`jnl`	Learning To Dive In Branch And Bound. CoRR Max B. Paulus, Andreas Krause
2023	J	`jnl`	Leveraging Demonstrations with Latent Space Priors. Trans. Mach. Learn. Res. Jonas Gehring, Deepak Gopinath, Jungdam Won, Andreas Krause, Gabriel Synnaeve, Nicolas Usunier
2023	A	`conf`	Lifelong bandit optimization: no prior and no regret. UAI Felix Schur, Parnian Kassraie, Jonas Rothfuss, Andreas Krause
2023	A*	`conf`	Likelihood Ratio Confidence Sets for Sequential Decision Making. NeurIPS Nicolas Emmenegger, Mojmir Mutny, Andreas Krause
2023	J	`jnl`	Likelihood Ratio Confidence Sets for Sequential Decision Making. CoRR Nicolas Emmenegger, Mojmír Mutný, Andreas Krause
2023	J	`jnl`	Linear Partial Monitoring for Sequential Decision Making: Algorithms, Regret Bounds and Applications. J. Mach. Learn. Res. Johannes Kirschner, Tor Lattimore, Andreas Krause
2023	J	`jnl`	Linear Partial Monitoring for Sequential Decision-Making: Algorithms, Regret Bounds and Applications. CoRR Johannes Kirschner, Tor Lattimore, Andreas Krause
2023	A*	`conf`	MARS: Meta-learning as Score Matching in the Function Space. ICLR Krunoslav Lehman Pavasovic, Jonas Rothfuss, Andreas Krause
2023	A*	`conf`	Model-based Causal Bayesian Optimization. ICLR Scott Sussex, Anastasia Makarova, Andreas Krause
2023	J	`jnl`	Model-based Causal Bayesian Optimization. CoRR Scott Sussex, Pier Giuseppe Sessa, Anastasiia Makarova, Andreas Krause
2023	A*	`conf`	Multitask Learning with No Regret: from Improved Confidence Bounds to Active Learning. NeurIPS Pier Giuseppe Sessa, Pierre Laforgue, Nicolò Cesa-Bianchi, Andreas Krause
2023	J	`jnl`	Multitask Learning with No Regret: from Improved Confidence Bounds to Active Learning. CoRR Pier Giuseppe Sessa, Pierre Laforgue, Nicolò Cesa-Bianchi, Andreas Krause
2023	A*	`conf`	Near-optimal Policy Identification in Active Reinforcement Learning. ICLR Xiang Li, Viraj Mehta, Johannes Kirschner, Ian Char, Willie Neiswanger, Jeff Schneider, Andreas Krause, Ilija Bogunovic
2023	A*	`conf`	Optimistic Active Exploration of Dynamical Systems. NeurIPS Bhavya Sukhija, Lenart Treven, Cansu Sancaktar, Sebastian Blaes, Stelian Coros, Andreas Krause
2023	J	`jnl`	Optimistic Active Exploration of Dynamical Systems. CoRR Bhavya Sukhija, Lenart Treven, Cansu Sancaktar, Sebastian Blaes, Stelian Coros, Andreas Krause
2023	J	`jnl`	Provably Learning Nash Policies in Constrained Markov Potential Games. CoRR Pragnya Alatur, Giorgia Ramponi, Niao He, Andreas Krause
2023	A*	`conf`	Replicable Bandits. ICLR Hossein Esfandiari, Alkis Kalavasis, Amin Karbasi, Andreas Krause, Vahab Mirrokni, Grigoris Velegkas
2023	A*	`conf`	Riemannian stochastic optimization methods avoid strict saddle points. NeurIPS Ya-Ping Hsieh, Mohammad Reza Karimi Jaghargh, Andreas Krause, Panayotis Mertikopoulos
2023	J	`jnl`	Riemannian stochastic optimization methods avoid strict saddle points. CoRR Ya-Ping Hsieh, Mohammad Reza Karimi, Andreas Krause, Panayotis Mertikopoulos
2023	J	`jnl`	Safe Deep RL for Intraoperative Planning of Pedicle Screw Placement. CoRR Yunke Ao, Hooman Esfandiari, Fabio Carrillo, Yarden As, Mazda Farshad, Benjamin F. Grewe, Andreas Krause, Philipp Fürnstahl
2023	J	`jnl`	Safe Model-Based Multi-Agent Mean-Field Reinforcement Learning. CoRR Matej Jusup, Barna Pásztor, Tadeusz Janik, Kenan Zhang, Francesco Corman, Andreas Krause, Ilija Bogunovic
2023	J	`jnl`	Safe Risk-Averse Bayesian Optimization for Controller Tuning. IEEE Robotics Autom. Lett. Christopher König, Miks Ozols, Anastasia Makarova, Efe C. Balta, Andreas Krause, Alisa Rupenyan
2023	J	`jnl`	Safe Risk-averse Bayesian Optimization for Controller Tuning. CoRR Christopher König, Miks Ozols, Anastasia Makarova, Efe C. Balta, Andreas Krause, Alisa Rupenyan
2023	J	`jnl`	Scalable PAC-Bayesian Meta-Learning via the PAC-Optimal Hyper-Posterior: From Theory to Practice. J. Mach. Learn. Res. Jonas Rothfuss, Martin Josifoski, Vincent Fortuin, Andreas Krause
2023	J	`jnl`	Sinkhorn Flow: A Continuous-Time Framework for Understanding and Generalizing the Sinkhorn Algorithm. CoRR Mohammad Reza Karimi, Ya-Ping Hsieh, Andreas Krause
2023	A*	`conf`	Stochastic Approximation Algorithms for Systems of Interacting Particles. NeurIPS Mohammad Reza Karimi Jaghargh, Ya-Ping Hsieh, Andreas Krause
2023	J	`jnl`	Submodular Reinforcement Learning. CoRR Manish Prajapat, Mojmír Mutný, Melanie N. Zeilinger, Andreas Krause
2023	A	`conf`	The Schrödinger Bridge between Gaussian Measures has a Closed Form. AISTATS Charlotte Bunne, Ya-Ping Hsieh, Marco Cuturi, Andreas Krause
2023	Misc	`conf`	Tuning Legged Locomotion Controllers via Safe Bayesian Optimization. CoRL Daniel Widmer, Dongho Kang, Bhavya Sukhija, Jonas Hübotter, Andreas Krause, Stelian Coros
2023	J	`jnl`	Tuning Legged Locomotion Controllers via Safe Bayesian Optimization. CoRR Daniel Widmer, Dongho Kang, Bhavya Sukhija, Jonas Hübotter, Andreas Krause, Stelian Coros
2023	J	`jnl`	Unbalanced Diffusion Schrödinger Bridge. CoRR Matteo Pariset, Ya-Ping Hsieh, Charlotte Bunne, Andreas Krause, Valentin De Bortoli
2022	J	`jnl`	A Dynamical System View of Langevin-Based Non-Convex Sampling. CoRR Mohammad Reza Karimi, Ya-Ping Hsieh, Andreas Krause
2022	A*	`conf`	A Robust Phased Elimination Algorithm for Corruption-Tolerant Gaussian Process Bandits. NeurIPS Ilija Bogunovic, Zihan Li, Andreas Krause, Jonathan Scarlett
2022	J	`jnl`	A Robust Phased Elimination Algorithm for Corruption-Tolerant Gaussian Process Bandits. CoRR Ilija Bogunovic, Zihan Li, Andreas Krause, Jonathan Scarlett
2022	A*	`conf`	Active Bayesian Causal Inference. NeurIPS Christian Toth, Lars Lorch, Christian Knoll, Andreas Krause, Franz Pernkopf, Robert Peharz, Julius von Kügelgen
2022	J	`jnl`	Active Bayesian Causal Inference. CoRR Christian Toth, Lars Lorch, Christian Knoll, Andreas Krause, Franz Pernkopf, Robert Peharz, Julius von Kügelgen
2022	A*	`conf`	Active Exploration for Inverse Reinforcement Learning. NeurIPS David Lindner, Andreas Krause, Giorgia Ramponi
2022	J	`jnl`	Active Exploration for Inverse Reinforcement Learning. CoRR David Lindner, Andreas Krause, Giorgia Ramponi
2022	J	`jnl`	Active Exploration via Experiment Design in Markov Chains. CoRR Mojmír Mutný, Tadeusz Janik, Andreas Krause
2022	A*	`conf`	Adaptive Gaussian Process Change Point Detection. ICML Edoardo Caldarelli, Philippe Wenk, Stefan Bauer, Andreas Krause
2022	A*	`conf`	Amortized Inference for Causal Structure Learning. NeurIPS Lars Lorch, Scott Sussex, Jonas Rothfuss, Andreas Krause, Bernhard Schölkopf
2022	J	`jnl`	Amortized Inference for Causal Structure Learning. CoRR Lars Lorch, Scott Sussex, Jonas Rothfuss, Andreas Krause, Bernhard Schölkopf
2022	—	`conf`	Automatic Termination for Hyperparameter Optimization. AutoML Anastasia Makarova, Huibin Shen, Valerio Perrone, Aaron Klein, Jean Baptiste Faddoul, Andreas Krause, Matthias W. Seeger, Cédric Archambeau
2022	J	`jnl`	BaCaDI: Bayesian Causal Discovery with Unknown Interventions. CoRR Alexander Hägele, Jonas Rothfuss, Lars Lorch, Vignesh Ram Somnath, Bernhard Schölkopf, Andreas Krause
2022	A*	`conf`	Constrained Policy Optimization via Bayesian World Models. ICLR Yarden As, Ilnura Usmanova, Sebastian Curi, Andreas Krause
2022	J	`jnl`	Constrained Policy Optimization via Bayesian World Models. CoRR Yarden As, Ilnura Usmanova, Sebastian Curi, Andreas Krause
2022	A	`conf`	Diversified Sampling for Batched Bayesian Optimization with Determinantal Point Processes. AISTATS Elvis Nava, Mojmir Mutny, Andreas Krause
2022	A*	`conf`	Efficient Model-based Multi-agent Reinforcement Learning via Optimistic Equilibrium Computation. ICML Pier Giuseppe Sessa, Maryam Kamgarpour, Andreas Krause
2022	J	`jnl`	Efficient Model-based Multi-agent Reinforcement Learning via Optimistic Equilibrium Computation. CoRR Pier Giuseppe Sessa, Maryam Kamgarpour, Andreas Krause
2022	A*	`conf`	Energy-Based Learning for Cooperative Games, with Applications to Valuation Problems in Machine Learning. ICLR Yatao Bian, Yu Rong, Tingyang Xu, Jiaxiang Wu, Andreas Krause, Junzhou Huang
2022	A*	`conf`	Experimental Design for Linear Functionals in Reproducing Kernel Hilbert Spaces. NeurIPS Mojmir Mutny, Andreas Krause
2022	J	`jnl`	Experimental Design for Linear Functionals in Reproducing Kernel Hilbert Spaces. CoRR Mojmír Mutný, Andreas Krause
2022	A*	`conf`	Graph Neural Network Bandits. NeurIPS Parnian Kassraie, Andreas Krause, Ilija Bogunovic
2022	J	`jnl`	Graph Neural Network Bandits. CoRR Parnian Kassraie, Andreas Krause, Ilija Bogunovic
2022	A*	`conf`	Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking. ICLR Octavian-Eugen Ganea, Xinyuan Huang, Charlotte Bunne, Yatao Bian, Regina Barzilay, Tommi S. Jaakkola, Andreas Krause
2022	J	`jnl`	Instance-Dependent Generalization Bounds via Optimal Transport. CoRR Songyan Hou, Parnian Kassraie, Anastasis Kratsios, Jonas Rothfuss, Andreas Krause
2022	A*	`conf`	Interactively Learning Preference Constraints in Linear Bandits. ICML David Lindner, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause
2022	J	`jnl`	Interactively Learning Preference Constraints in Linear Bandits. CoRR David Lindner, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause
2022	J	`jnl`	Invariant Causal Mechanisms through Distribution Matching. CoRR Mathieu Chevalley, Charlotte Bunne, Andreas Krause, Stefan Bauer
2022	J	`jnl`	Isotropic Gaussian Processes on Finite Spaces of Graphs. CoRR Viacheslav Borovitskiy, Mohammad Reza Karimi, Vignesh Ram Somnath, Andreas Krause
2022	A*	`conf`	Learning Long-Term Crop Management Strategies with CyclesGym. NeurIPS Matteo Turchetta, Luca Corinzia, Scott Sussex, Amanda Burton, Juan Herrera, Ioannis N. Athanasiadis, Joachim M. Buhmann, Andreas Krause
2022	J	`jnl`	Learning To Cut By Looking Ahead: Cutting Plane Selection via Imitation Learning. CoRR Max B. Paulus, Giulia Zarpellon, Andreas Krause, Laurent Charlin, Chris J. Maddison
2022	A*	`conf`	Learning to Cut by Looking Ahead: Cutting Plane Selection via Imitation Learning. ICML Max B. Paulus, Giulia Zarpellon, Andreas Krause, Laurent Charlin, Chris J. Maddison
2022	J	`jnl`	Leveraging Demonstrations with Latent Space Priors. CoRR Jonas Gehring, Deepak Gopinath, Jungdam Won, Andreas Krause, Gabriel Synnaeve, Nicolas Usunier
2022	J	`jnl`	Lifelong Bandit Optimization: No Prior and No Regret. CoRR Felix Schur, Parnian Kassraie, Jonas Rothfuss, Andreas Krause
2022	J	`jnl`	Log Barriers for Safe Black-box Optimization with Application to Safe Reinforcement Learning. CoRR Ilnura Usmanova, Yarden As, Maryam Kamgarpour, Andreas Krause
2022	J	`jnl`	MARS: Meta-Learning as Score Matching in the Function Space. CoRR Krunoslav Lehman Pavasovic, Jonas Rothfuss, Andreas Krause
2022	A*	`conf`	Meta-Learning Hypothesis Spaces for Sequential Decision-making. ICML Parnian Kassraie, Jonas Rothfuss, Andreas Krause
2022	J	`jnl`	Meta-Learning Hypothesis Spaces for Sequential Decision-making. CoRR Parnian Kassraie, Jonas Rothfuss, Andreas Krause
2022	Misc	`conf`	Meta-Learning Priors for Safe Bayesian Optimization. CoRL Jonas Rothfuss, Christopher König, Alisa Rupenyan, Andreas Krause
2022	J	`jnl`	Meta-Learning Priors for Safe Bayesian Optimization. CoRR Jonas Rothfuss, Christopher König, Alisa Rupenyan, Andreas Krause
2022	J	`jnl`	Model-based Causal Bayesian Optimization. CoRR Scott Sussex, Anastasiia Makarova, Andreas Krause
2022	A*	`conf`	Movement Penalized Bayesian Optimization with Application to Wind Energy Systems. NeurIPS Shyam Sundhar Ramesh, Pier Giuseppe Sessa, Andreas Krause, Ilija Bogunovic
2022	J	`jnl`	Movement Penalized Bayesian Optimization with Application to Wind Energy Systems. CoRR Shyam Sundhar Ramesh, Pier Giuseppe Sessa, Andreas Krause, Ilija Bogunovic
2022	J	`jnl`	Multi-Scale Representation Learning on Proteins. CoRR Vignesh Ram Somnath, Charlotte Bunne, Andreas Krause
2022	A*	`conf`	Near-Optimal Multi-Agent Learning for Safe Coverage Control. NeurIPS Manish Prajapat, Matteo Turchetta, Melanie N. Zeilinger, Andreas Krause
2022	J	`jnl`	Near-Optimal Multi-Agent Learning for Safe Coverage Control. CoRR Manish Prajapat, Matteo Turchetta, Melanie N. Zeilinger, Andreas Krause
2022	J	`jnl`	Near-optimal Policy Identification in Active Reinforcement Learning. CoRR Xiang Li, Viraj Mehta, Johannes Kirschner, Ian Char, Willie Neiswanger, Jeff Schneider, Andreas Krause, Ilija Bogunovic
2022	A	`conf`	Neural Contextual Bandits without Regret. AISTATS Parnian Kassraie, Andreas Krause
2022	J	`jnl`	PAC-Bayesian Meta-Learning: From Theory to Practice. CoRR Jonas Rothfuss, Martin Josifoski, Vincent Fortuin, Andreas Krause
2022	A	`conf`	Proximal Optimal Transport Modeling of Population Dynamics. AISTATS Charlotte Bunne, Laetitia Papaxanthos, Andreas Krause, Marco Cuturi
2022	J	`jnl`	Recovering Stochastic Dynamics via Gaussian Schrödinger Bridges. CoRR Charlotte Bunne, Ya-Ping Hsieh, Marco Cuturi, Andreas Krause
2022	J	`jnl`	Reproducible Bandits. CoRR Hossein Esfandiari, Alkis Kalavasis, Amin Karbasi, Andreas Krause, Vahab Mirrokni, Grigoris Velegkas
2022	—	`conf`	Safe Reinforcement Learning via Confidence-Based Filters. CDC Sebastian Curi, Armin Lederer, Sandra Hirche, Andreas Krause
2022	J	`jnl`	Safe Reinforcement Learning via Confidence-Based Filters. CoRR Sebastian Curi, Armin Lederer, Sandra Hirche, Andreas Krause
2022	J	`jnl`	Scalable Safe Exploration for Global Optimization of Dynamical Systems. CoRR Bhavya Sukhija, Matteo Turchetta, David Lindner, Andreas Krause, Sebastian Trimpe, Dominik Baumann
2022	A	`conf`	Sensing Cox Processes via Posterior Sampling and Positive Bases. AISTATS Mojmir Mutny, Andreas Krause
2022	A*	`conf`	Supervised Training of Conditional Monge Maps. NeurIPS Charlotte Bunne, Andreas Krause, Marco Cuturi
2022	J	`jnl`	Supervised Training of Conditional Monge Maps. CoRR Charlotte Bunne, Andreas Krause, Marco Cuturi
2022	A*	`conf`	The Dynamics of Riemannian Robbins-Monro Algorithms. COLT Mohammad Reza Karimi, Ya-Ping Hsieh, Panayotis Mertikopoulos, Andreas Krause
2022	J	`jnl`	The Dynamics of Riemannian Robbins-Monro Algorithms. CoRR Mohammad Reza Karimi, Ya-Ping Hsieh, Panayotis Mertikopoulos, Andreas Krause
2022	J	`jnl`	Tuning Particle Accelerators with Safety Constraints using Bayesian Optimization. CoRR Johannes Kirschner, Mojmír Mutný, Andreas Krause, Jaime Coello de Portugal, Nicole Hiller, Jochem Snuverink
2021	C	`conf`	A Human-in-the-loop Framework to Construct Context-aware Mathematical Notions of Outcome Fairness. AIES Mohammad Yaghini, Andreas Krause, Hoda Heidari
2021	A*	`conf`	Addressing the Long-term Impact of ML Decisions via Policy Regret. IJCAI David Lindner, Hoda Heidari, Andreas Krause
2021	J	`jnl`	Addressing the Long-term Impact of ML Decisions via Policy Regret. CoRR David Lindner, Hoda Heidari, Andreas Krause
2021	J	`jnl`	Bias-Robust Bayesian Optimization via Dueling Bandit. CoRR Johannes Kirschner, Andreas Krause
2021	A*	`conf`	Bias-Robust Bayesian Optimization via Dueling Bandits. ICML Johannes Kirschner, Andreas Krause
2021	A*	`conf`	Cherry-Picking Gradients: Learning Low-Rank Embeddings of Visual Data via Differentiable Cross-Approximation. ICCV Mikhail Usvyatsov, Anastasia Makarova, Rafael Ballester-Ripoll, Maxim V. Rakhuba, Andreas Krause, Konrad Schindler
2021	J	`jnl`	Cherry-Picking Gradients: Learning Low-Rank Embeddings of Visual Data via Differentiable Cross-Approximation. CoRR Mikhail Usvyatsov, Anastasia Makarova, Rafael Ballester-Ripoll, Maxim V. Rakhuba, Andreas Krause, Konrad Schindler
2021	A*	`conf`	Combining Pessimism with Optimism for Robust and Efficient Model-Based Deep Reinforcement Learning. ICML Sebastian Curi, Ilija Bogunovic, Andreas Krause
2021	J	`jnl`	Combining Pessimism with Optimism for Robust and Efficient Model-Based Deep Reinforcement Learning. CoRR Sebastian Curi, Ilija Bogunovic, Andreas Krause
2021	J	`jnl`	Contextual Games: Multi-Agent Learning with Side Information. CoRR Pier Giuseppe Sessa, Ilija Bogunovic, Andreas Krause, Maryam Kamgarpour
2021	J	`jnl`	Data Summarization via Bilevel Optimization. CoRR Zalán Borsos, Mojmír Mutný, Marco Tagliasacchi, Andreas Krause
2021	A*	`conf`	DiBS: Differentiable Bayesian Structure Learning. NeurIPS Lars Lorch, Jonas Rothfuss, Bernhard Schölkopf, Andreas Krause
2021	J	`jnl`	DiBS: Differentiable Bayesian Structure Learning. CoRR Lars Lorch, Jonas Rothfuss, Bernhard Schölkopf, Andreas Krause
2021	A*	`conf`	Distributional Gradient Matching for Learning Uncertain Neural Dynamics Models. NeurIPS Lenart Treven, Philippe Wenk, Florian Dörfler, Andreas Krause
2021	J	`jnl`	Distributional Gradient Matching for Learning Uncertain Neural Dynamics Models. CoRR Lenart Treven, Philippe Wenk, Florian Dörfler, Andreas Krause
2021	J	`jnl`	Diversified Sampling for Batched Bayesian Optimization with Determinantal Point Processes. CoRR Elvis Nava, Mojmír Mutný, Andreas Krause
2021	J	`jnl`	Efficient Model-Based Multi-Agent Mean-Field Reinforcement Learning. CoRR Barna Pásztor, Ilija Bogunovic, Andreas Krause
2021	B	`conf`	Efficient Pure Exploration for Combinatorial Bandits with Semi-Bandit Feedback. ALT Marc Jourdan, Mojmír Mutný, Johannes Kirschner, Andreas Krause
2021	J	`jnl`	Efficient Pure Exploration for Combinatorial Bandits with Semi-Bandit Feedback. CoRR Marc Jourdan, Mojmír Mutný, Johannes Kirschner, Andreas Krause
2021	J	`jnl`	Energy-Based Learning for Cooperative Games, with Applications to Feature/Data/Model Valuations. CoRR Yatao Bian, Yu Rong, Tingyang Xu, Jiaxiang Wu, Andreas Krause, Junzhou Huang
2021	A*	`conf`	Fast Projection Onto Convex Smooth Constraints. ICML Ilnura Usmanova, Maryam Kamgarpour, Andreas Krause, Kfir Y. Levy
2021	A*	`conf`	Hierarchical Skills for Efficient Exploration. NeurIPS Jonas Gehring, Gabriel Synnaeve, Andreas Krause, Nicolas Usunier
2021	J	`jnl`	Hierarchical Skills for Efficient Exploration. CoRR Jonas Gehring, Gabriel Synnaeve, Andreas Krause, Nicolas Usunier
2021	J	`jnl`	Incentive-Compatible Forecasting Competitions. CoRR Jens Witkowski, Rupert Freeman, Jennifer Wortman Vaughan, David M. Pennock, Andreas Krause
2021	J	`jnl`	Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking. CoRR Octavian-Eugen Ganea, Xinyuan Huang, Charlotte Bunne, Yatao Bian, Regina Barzilay, Tommi S. Jaakkola, Andreas Krause
2021	A*	`conf`	Information Directed Reward Learning for Reinforcement Learning. NeurIPS David Lindner, Matteo Turchetta, Sebastian Tschiatschek, Kamil Ciosek, Andreas Krause
2021	J	`jnl`	Information Directed Reward Learning for Reinforcement Learning. CoRR David Lindner, Matteo Turchetta, Sebastian Tschiatschek, Kamil Ciosek, Andreas Krause
2021	J	`jnl`	JKOnet: Proximal Optimal Transport Modeling of Population Dynamics. CoRR Charlotte Bunne, Laetitia Meng-Papaxanthos, Andreas Krause, Marco Cuturi
2021	A*	`conf`	Learning Graph Models for Retrosynthesis Prediction. NeurIPS Vignesh Ram Somnath, Charlotte Bunne, Connor W. Coley, Andreas Krause, Regina Barzilay
2021	A*	`conf`	Learning Set Functions that are Sparse in Non-Orthogonal Fourier Bases. AAAI Chris Wendler, Andisheh Amrollahi, Bastian Seifert, Andreas Krause, Markus Püschel
2021	—	`conf`	Learning Stabilizing Controllers for Unstable Linear Quadratic Regulators from a Single Trajectory. L4DC Lenart Treven, Sebastian Curi, Mojmír Mutný, Andreas Krause
2021	A*	`conf`	Learning Stable Deep Dynamics Models for Partially Observed or Delayed Dynamical Systems. NeurIPS Andreas Schlaginhaufen, Philippe Wenk, Andreas Krause, Florian Dörfler
2021	J	`jnl`	Learning Stable Deep Dynamics Models for Partially Observed or Delayed Dynamical Systems. CoRR Andreas Schlaginhaufen, Philippe Wenk, Andreas Krause, Florian Dörfler
2021	A	`conf`	Logistic Q-Learning. AISTATS Joan Bas-Serrano, Sebastian Curi, Andreas Krause, Gergely Neu
2021	A*	`conf`	Meta-Learning Reliable Priors in the Function Space. NeurIPS Jonas Rothfuss, Dominique Heyn, Jinfan Chen, Andreas Krause
2021	J	`jnl`	Meta-Learning Reliable Priors in the Function Space. CoRR Jonas Rothfuss, Dominique Heyn, Jinfan Chen, Andreas Krause
2021	A*	`conf`	Misspecified Gaussian Process Bandit Optimization. NeurIPS Ilija Bogunovic, Andreas Krause
2021	J	`jnl`	Misspecified Gaussian Process Bandit Optimization. CoRR Ilija Bogunovic, Andreas Krause
2021	A*	`conf`	Multi-Scale Representation Learning on Proteins. NeurIPS Vignesh Ram Somnath, Charlotte Bunne, Andreas Krause
2021	A*	`conf`	Near-Optimal Multi-Perturbation Experimental Design for Causal Structure Learning. NeurIPS Scott Sussex, Caroline Uhler, Andreas Krause
2021	J	`jnl`	Near-Optimal Multi-Perturbation Experimental Design for Causal Structure Learning. CoRR Scott Sussex, Andreas Krause, Caroline Uhler
2021	J	`jnl`	Neural Contextual Bandits without Regret. CoRR Parnian Kassraie, Andreas Krause
2021	A*	`conf`	No-regret Algorithms for Capturing Events in Poisson Point Processes. ICML Mojmir Mutny, Andreas Krause
2021	A	`conf`	Online Active Model Selection for Pre-trained Classifiers. AISTATS Mohammad Reza Karimi, Nezihe Merve Gürel, Bojan Karlas, Johannes Rausch, Ce Zhang, Andreas Krause
2021	A*	`conf`	Online Submodular Resource Allocation with Applications to Rebalancing Shared Mobility Systems. ICML Pier Giuseppe Sessa, Ilija Bogunovic, Andreas Krause, Maryam Kamgarpour
2021	J	`jnl`	Overfitting in Bayesian Optimization: an empirical study and early-stopping solution. CoRR Anastasia Makarova, Huibin Shen, Valerio Perrone, Aaron Klein, Jean Baptiste Faddoul, Andreas Krause, Matthias W. Seeger, Cédric Archambeau
2021	A*	`conf`	PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees. ICML Jonas Rothfuss, Vincent Fortuin, Martin Josifoski, Andreas Krause
2021	A*	`conf`	PopSkipJump: Decision-Based Attack for Probabilistic Classifiers. ICML Carl-Johann Simon-Gabriel, Noman Ahmed Sheikh, Andreas Krause
2021	J	`jnl`	PopSkipJump: Decision-Based Attack for Probabilistic Classifiers. CoRR Carl-Johann Simon-Gabriel, Noman Ahmed Sheikh, Andreas Krause
2021	A*	`conf`	Rao-Blackwellizing the Straight-Through Gumbel-Softmax Gradient Estimator. ICLR Max B. Paulus, Chris J. Maddison, Andreas Krause
2021	A*	`conf`	Regret Bounds for Gaussian-Process Optimization in Large Domains. NeurIPS Manuel Wüthrich, Bernhard Schölkopf, Andreas Krause
2021	J	`jnl`	Regret Bounds for Gaussian-Process Optimization in Large Domains. CoRR Manuel Wüthrich, Bernhard Schölkopf, Andreas Krause
2021	A*	`conf`	Risk-Averse Offline Reinforcement Learning. ICLR Núria Armengol Urpí, Sebastian Curi, Andreas Krause
2021	J	`jnl`	Risk-Averse Offline Reinforcement Learning. CoRR Núria Armengol Urpi, Sebastian Curi, Andreas Krause
2021	A*	`conf`	Risk-averse Heteroscedastic Bayesian Optimization. NeurIPS Anastasia Makarova, Ilnura Usmanova, Ilija Bogunovic, Andreas Krause
2021	J	`jnl`	Risk-averse Heteroscedastic Bayesian Optimization. CoRR Anastasia Makarova, Ilnura Usmanova, Ilija Bogunovic, Andreas Krause
2021	A*	`conf`	Robust Generalization despite Distribution Shift via Minimum Discriminating Information. NeurIPS Tobias Sutter, Andreas Krause, Daniel Kuhn
2021	J	`jnl`	Robust Generalization despite Distribution Shift via Minimum Discriminating Information. CoRR Tobias Sutter, Andreas Krause, Daniel Kuhn
2021	A*	`conf`	Safe and Efficient Model-free Adaptive Control via Bayesian Optimization. ICRA Christopher König, Matteo Turchetta, John Lygeros, Alisa Rupenyan, Andreas Krause
2021	J	`jnl`	Safe and Efficient Model-free Adaptive Control via Bayesian Optimization. CoRR Christopher König, Matteo Turchetta, John Lygeros, Alisa Rupenyan, Andreas Krause
2021	Misc	`conf`	Semi-Supervised Batch Active Learning Via Bilevel Optimization. ICASSP Zalán Borsos, Marco Tagliasacchi, Andreas Krause
2021	J	`jnl`	Sensing Cox Processes via Posterior Sampling and Positive Bases. CoRR Mojmír Mutný, Andreas Krause
2021	A	`conf`	Stochastic Linear Bandits Robust to Adversarial Attacks. AISTATS Ilija Bogunovic, Arpan Losalka, Andreas Krause, Jonathan Scarlett
2020	A*	`conf`	A Real-Robot Dataset for Assessing Transferability of Learned Dynamics Models. ICRA Diego Agudelo-España, Andrii Zadaianchuk, Philippe Wenk, Aditya Garg, Joel Akpo, Felix Grimminger, Julian Viereck, Maximilien Naveau, Ludovic Righetti, Georg Martius, Andreas Krause, Bernhard Schölkopf, Stefan Bauer, Manuel Wüthrich
2020	A*	`conf`	Adaptive Sampling for Stochastic Risk-Averse Learning. NeurIPS Sebastian Curi, Kfir Y. Levy, Stefanie Jegelka, Andreas Krause
2020	A*	`conf`	Contextual Games: Multi-Agent Learning with Side Information. NeurIPS Pier Giuseppe Sessa, Ilija Bogunovic, Andreas Krause, Maryam Kamgarpour
2020	J	`jnl`	Continuous Submodular Function Maximization. CoRR Yatao Bian, Joachim M. Buhmann, Andreas Krause
2020	A	`conf`	Convergence Analysis of Block Coordinate Algorithms with Determinantal Sampling. AISTATS Mojmir Mutny, Michal Derezinski, Andreas Krause
2020	A*	`conf`	Coresets via Bilevel Optimization for Continual Learning and Streaming. NeurIPS Zalán Borsos, Mojmir Mutny, Andreas Krause
2020	J	`jnl`	Coresets via Bilevel Optimization for Continual Learning and Streaming. CoRR Zalán Borsos, Mojmír Mutný, Andreas Krause
2020	A	`conf`	Corruption-Tolerant Gaussian Process Bandit Optimization. AISTATS Ilija Bogunovic, Andreas Krause, Jonathan Scarlett
2020	J	`jnl`	Corruption-Tolerant Gaussian Process Bandit Optimization. CoRR Ilija Bogunovic, Andreas Krause, Jonathan Scarlett
2020	A	`conf`	Distributionally Robust Bayesian Optimization. AISTATS Johannes Kirschner, Ilija Bogunovic, Stefanie Jegelka, Andreas Krause
2020	J	`jnl`	Distributionally Robust Bayesian Optimization. CoRR Johannes Kirschner, Ilija Bogunovic, Stefanie Jegelka, Andreas Krause
2020	A*	`conf`	Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning. NeurIPS Sebastian Curi, Felix Berkenkamp, Andreas Krause
2020	J	`jnl`	Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning. CoRR Sebastian Curi, Felix Berkenkamp, Andreas Krause
2020	A*	`conf`	Experimental Design for Optimization of Orthogonal Projection Pursuit Models. AAAI Mojmir Mutny, Johannes Kirschner, Andreas Krause
2020	A*	`conf`	From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models. ICML Aytunc Sahin, Yatao Bian, Joachim M. Buhmann, Andreas Krause
2020	J	`jnl`	From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models. CoRR Aytunc Sahin, Yatao Bian, Joachim M. Buhmann, Andreas Krause
2020	A*	`conf`	Gradient Estimation with Stochastic Softmax Tricks. NeurIPS Max B. Paulus, Dami Choi, Daniel Tarlow, Andreas Krause, Chris J. Maddison
2020	J	`jnl`	Gradient Estimation with Stochastic Softmax Tricks. CoRR Max B. Paulus, Dami Choi, Daniel Tarlow, Andreas Krause, Chris J. Maddison
2020	—	`conf`	Hierarchical Image Classification using Entailment Cone Embeddings. CVPR Workshops Ankit Dhall, Anastasia Makarova, Octavian Ganea, Dario Pavllo, Michael Greeff, Andreas Krause
2020	J	`jnl`	Hierarchical Image Classification using Entailment Cone Embeddings. CoRR Ankit Dhall, Anastasia Makarova, Octavian Ganea, Dario Pavllo, Michael Greeff, Andreas Krause
2020	A*	`conf`	Information Directed Sampling for Linear Partial Monitoring. COLT Johannes Kirschner, Tor Lattimore, Andreas Krause
2020	J	`jnl`	Information Directed Sampling for Linear Partial Monitoring. CoRR Johannes Kirschner, Tor Lattimore, Andreas Krause
2020	J	`jnl`	Learning Controllers for Unstable Linear Quadratic Regulators from a Single Trajectory. CoRR Lenart Treven, Sebastian Curi, Mojmir Mutny, Andreas Krause
2020	J	`jnl`	Learning Graph Models for Template-Free Retrosynthesis. CoRR Vignesh Ram Somnath, Charlotte Bunne, Connor W. Coley, Andreas Krause, Regina Barzilay
2020	J	`jnl`	Learning Set Functions that are Sparse in Non-Orthogonal Fourier Bases. CoRR Chris Wendler, Andisheh Amrollahi, Bastian Seifert, Andreas Krause, Markus Püschel
2020	A*	`conf`	Learning to Play Sequential Games versus Unknown Opponents. NeurIPS Pier Giuseppe Sessa, Ilija Bogunovic, Maryam Kamgarpour, Andreas Krause
2020	J	`jnl`	Learning to Play Sequential Games versus Unknown Opponents. CoRR Pier Giuseppe Sessa, Ilija Bogunovic, Maryam Kamgarpour, Andreas Krause
2020	J	`jnl`	Logistic $Q$-Learning. CoRR Joan Bas-Serrano, Sebastian Curi, Andreas Krause, Gergely Neu
2020	A	`conf`	Mixed Strategies for Robust Optimization of Unknown Objectives. AISTATS Pier Giuseppe Sessa, Ilija Bogunovic, Maryam Kamgarpour, Andreas Krause
2020	J	`jnl`	Mixed Strategies for Robust Optimization of Unknown Objectives. CoRR Pier Giuseppe Sessa, Ilija Bogunovic, Maryam Kamgarpour, Andreas Krause
2020	A*	`conf`	Mixed-Variable Bayesian Optimization. IJCAI Erik A. Daxberger, Anastasia Makarova, Matteo Turchetta, Andreas Krause
2020	J	`jnl`	Multi-Player Bandits: The Adversarial Case. J. Mach. Learn. Res. Pragnya Alatur, Kfir Y. Levy, Andreas Krause
2020	A*	`conf`	ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems. AAAI Philippe Wenk, Gabriele Abbati, Michael A. Osborne, Bernhard Schölkopf, Andreas Krause, Stefan Bauer
2020	J	`jnl`	Online Active Model Selection for Pre-trained Classifiers. CoRR Mohammad Reza Karimi, Nezihe Merve Gürel, Bojan Karlas, Johannes Rausch, Ce Zhang, Andreas Krause
2020	J	`jnl`	PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees. CoRR Jonas Rothfuss, Vincent Fortuin, Andreas Krause
2020	J	`jnl`	Rao-Blackwellizing the Straight-Through Gumbel-Softmax Gradient Estimator. CoRR Max B. Paulus, Chris J. Maddison, Andreas Krause
2020	A*	`conf`	Robust Model-free Reinforcement Learning with Multi-objective Bayesian Optimization. ICRA Matteo Turchetta, Andreas Krause, Sebastian Trimpe
2020	J	`jnl`	SLEIPNIR: Deterministic and Provably Accurate Feature Expansion for Gaussian Process Regression with Derivatives. CoRR Emmanouil Angelis, Philippe Wenk, Bernhard Schölkopf, Stefan Bauer, Andreas Krause
2020	A*	`conf`	Safe Reinforcement Learning via Curriculum Induction. NeurIPS Matteo Turchetta, Andrey Kolobov, Shital Shah, Andreas Krause, Alekh Agarwal
2020	J	`jnl`	Safe Reinforcement Learning via Curriculum Induction. CoRR Matteo Turchetta, Andrey Kolobov, Shital Shah, Andreas Krause, Alekh Agarwal
2020	—	`conf`	Safe non-smooth black-box optimization with application to policy search. L4DC Ilnura Usmanova, Andreas Krause, Maryam Kamgarpour
2020	J	`jnl`	Semi-supervised Batch Active Learning via Bilevel Optimization. CoRR Zalán Borsos, Marco Tagliasacchi, Andreas Krause
2020	J	`jnl`	Stochastic Linear Bandits Robust to Adversarial Attacks. CoRR Ilija Bogunovic, Arpan Losalka, Andreas Krause, Jonathan Scarlett
2020	—	`conf`	Structured Variational Inference in Partially Observable UnstableGaussian Process State Space Models. L4DC Sebastian Curi, Silvan Melchior, Felix Berkenkamp, Andreas Krause
2019	A*	`conf`	A Domain Agnostic Measure for Monitoring and Evaluating GANs. NeurIPS Paulina Grnarova, Kfir Y. Levy, Aurélien Lucchi, Nathanaël Perraudin, Ian J. Goodfellow, Thomas Hofmann, Andreas Krause
2019	J	`jnl`	A Human-in-the-loop Framework to Construct Context-dependent Mathematical Formulations of Fairness. CoRR Mohammad Yaghini, Hoda Heidari, Andreas Krause
2019	—	`conf`	A Moral Framework for Understanding Fair ML through Economic Models of Equality of Opportunity. FAT Hoda Heidari, Michele Loi, Krishna P. Gummadi, Andreas Krause
2019	J	`jnl`	AReS and MaRS - Adversarial and MMD-Minimizing Regression for SDEs. CoRR Gabriele Abbati, Philippe Wenk, Stefan Bauer, Michael A. Osborne, Andreas Krause, Bernhard Schölkopf
2019	A*	`conf`	AReS and MaRS Adversarial and MMD-Minimizing Regression for SDEs. ICML Gabriele Abbati, Philippe Wenk, Michael A. Osborne, Andreas Krause, Bernhard Schölkopf, Stefan Bauer
2019	—	`conf`	Adaptive Input Estimation in Linear Dynamical Systems with Applications to Learning-from-Observations. CDC Sebastian Curi, Kfir Y. Levy, Andreas Krause
2019	J	`jnl`	Adaptive Sampling for Stochastic Risk-Averse Learning. CoRR Sebastian Curi, Kfir Y. Levy, Stefanie Jegelka, Andreas Krause
2019	A*	`conf`	Adaptive Sequence Submodularity. NeurIPS Marko Mitrovic, Ehsan Kazemi, Moran Feldman, Andreas Krause, Amin Karbasi
2019	J	`jnl`	Adaptive Sequence Submodularity. CoRR Marko Mitrovic, Ehsan Kazemi, Moran Feldman, Andreas Krause, Amin Karbasi
2019	A*	`conf`	Adaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces. ICML Johannes Kirschner, Mojmir Mutny, Nicole Hiller, Rasmus Ischebeck, Andreas Krause
2019	J	`jnl`	Adaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces. CoRR Johannes Kirschner, Mojmír Mutný, Nicole Hiller, Rasmus Ischebeck, Andreas Krause
2019	A	`conf`	Bounding Inefficiency of Equilibria in Continuous Actions Games using Submodularity and Curvature. AISTATS Pier Giuseppe Sessa, Maryam Kamgarpour, Andreas Krause
2019	J	`jnl`	Bounding Inefficiency of Equilibria in Continuous Actions Games using Submodularity and Curvature. CoRR Pier Giuseppe Sessa, Maryam Kamgarpour, Andreas Krause
2019	A	`conf`	Consistent Online Optimization: Convex and Submodular. AISTATS Mohammad Reza Karimi Jaghargh, Andreas Krause, Silvio Lattanzi, Sergei Vassilvitskii
2019	J	`jnl`	Convergence Analysis of the Randomized Newton Method with Determinantal Sampling. CoRR Mojmír Mutný, Michal Derezinski, Andreas Krause
2019	A*	`conf`	Efficiently Learning Fourier Sparse Set Functions. NeurIPS Andisheh Amrollahi, Amir Zandieh, Michael Kapralov, Andreas Krause
2019	A	`conf`	Fast Gaussian process based gradient matching for parameter identification in systems of nonlinear ODEs. AISTATS Philippe Wenk, Alkis Gotovos, Stefan Bauer, Nico S. Gorbach, Andreas Krause, Joachim M. Buhmann
2019	—	`conf`	Information-Directed Exploration for Deep Reinforcement Learning. ICLR (Poster) Nikolay Nikolov, Johannes Kirschner, Felix Berkenkamp, Andreas Krause
2019	A*	`conf`	Learning Generative Models across Incomparable Spaces. ICML Charlotte Bunne, David Alvarez-Melis, Andreas Krause, Stefanie Jegelka
2019	J	`jnl`	Learning Generative Models across Incomparable Spaces. CoRR Charlotte Bunne, David Alvarez-Melis, Andreas Krause, Stefanie Jegelka
2019	—	`conf`	Learning to Compensate Photovoltaic Power Fluctuations from Images of the Sky by Imitating an Optimal Policy. ECC Robin Spiess, Felix Berkenkamp, Andreas Krause, Jan Poland
2019	J	`jnl`	Learning-based Model Predictive Control for Safe Exploration and Reinforcement Learning. CoRR Torsten Koller, Felix Berkenkamp, Matteo Turchetta, Joschka Boedecker, Andreas Krause
2019	J	`jnl`	Log Barriers for Safe Non-convex Black-box Optimization. CoRR Ilnura Usmanova, Andreas Krause, Maryam Kamgarpour
2019	A*	`conf`	Mathematical Notions vs. Human Perception of Fairness: A Descriptive Approach to Fairness for Machine Learning. KDD Megha Srivastava, Hoda Heidari, Andreas Krause
2019	J	`jnl`	Mathematical Notions vs. Human Perception of Fairness: A Descriptive Approach to Fairness for Machine Learning. CoRR Megha Srivastava, Hoda Heidari, Andreas Krause
2019	J	`jnl`	Mixed-Variable Bayesian Optimization. CoRR Erik A. Daxberger, Anastasia Makarova, Matteo Turchetta, Andreas Krause
2019	A*	`conf`	Mobile Robotic Painting of Texture. ICRA Majed El Helou, Stephan Mandt, Andreas Krause, Paul A. Beardsley
2019	J	`jnl`	Multi-Player Bandits: The Adversarial Case. CoRR Pragnya Alatur, Kfir Y. Levy, Andreas Krause
2019	J	`jnl`	No-Regret Bayesian Optimization with Unknown Hyperparameters. J. Mach. Learn. Res. Felix Berkenkamp, Angela P. Schoellig, Andreas Krause
2019	A*	`conf`	No-Regret Learning in Unknown Games with Correlated Payoffs. NeurIPS Pier Giuseppe Sessa, Ilija Bogunovic, Maryam Kamgarpour, Andreas Krause
2019	J	`jnl`	No-Regret Learning in Unknown Games with Correlated Payoffs. CoRR Pier Giuseppe Sessa, Ilija Bogunovic, Maryam Kamgarpour, Andreas Krause
2019	J	`jnl`	No-regret Bayesian Optimization with Unknown Hyperparameters. CoRR Felix Berkenkamp, Angela P. Schoellig, Andreas Krause
2019	J	`jnl`	Noise Regularization for Conditional Density Estimation. CoRR Jonas Rothfuss, Fábio Ferreira, Simon Boehm, Simon Walther, Maxim Ulrich, Tamim Asfour, Andreas Krause
2019	J	`jnl`	ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems. CoRR Philippe Wenk, Gabriele Abbati, Stefan Bauer, Michael A. Osborne, Andreas Krause, Bernhard Schölkopf
2019	A*	`conf`	Online Variance Reduction with Mixtures. ICML Zalán Borsos, Sebastian Curi, Kfir Yehuda Levy, Andreas Krause
2019	J	`jnl`	Online Variance Reduction with Mixtures. CoRR Zalán Borsos, Sebastian Curi, Kfir Y. Levy, Andreas Krause
2019	A*	`conf`	Optimal Continuous DR-Submodular Maximization and Applications to Provable Mean Field Inference. ICML Yatao An Bian, Joachim M. Buhmann, Andreas Krause
2019	J	`jnl`	Predicting program properties from 'big code'. Commun. ACM Veselin Raychev, Martin T. Vechev, Andreas Krause
2019	A	`conf`	Projection Free Online Learning over Smooth Sets. AISTATS Kfir Y. Levy, Andreas Krause
2019	J	`jnl`	Robust Model-free Reinforcement Learning with Multi-objective Bayesian Optimization. CoRR Matteo Turchetta, Andreas Krause, Sebastian Trimpe
2019	A*	`conf`	Safe Contextual Bayesian Optimization for Sustainable Room Temperature PID Control Tuning. IJCAI Marcello Fiducioso, Sebastian Curi, Benedikt Schumacher, Markus Gwerder, Andreas Krause
2019	J	`jnl`	Safe Contextual Bayesian Optimization for Sustainable Room Temperature PID Control Tuning. CoRR Marcello Fiducioso, Sebastian Curi, Benedikt Schumacher, Markus Gwerder, Andreas Krause
2019	A	`conf`	Safe Convex Learning under Uncertain Constraints. AISTATS Ilnura Usmanova, Andreas Krause, Maryam Kamgarpour
2019	A*	`conf`	Safe Exploration for Interactive Machine Learning. NeurIPS Matteo Turchetta, Felix Berkenkamp, Andreas Krause
2019	J	`jnl`	Safe Exploration for Interactive Machine Learning. CoRR Matteo Turchetta, Felix Berkenkamp, Andreas Krause
2019	J	`jnl`	Safe non-smooth black-box optimization with application to policy search. CoRR Ilnura Usmanova, Andreas Krause, Maryam Kamgarpour
2019	A*	`conf`	Stochastic Bandits with Context Distributions. NeurIPS Johannes Kirschner, Andreas Krause
2019	J	`jnl`	Stochastic Bandits with Context Distributions. CoRR Johannes Kirschner, Andreas Krause
2019	J	`jnl`	Structured Variational Inference in Unstable Gaussian Process State Space Models. CoRR Silvan Melchior, Felix Berkenkamp, Sebastian Curi, Andreas Krause
2019	A*	`conf`	Teaching Multiple Concepts to a Forgetful Learner. NeurIPS Anette Hunziker, Yuxin Chen, Oisin Mac Aodha, Manuel Gomez Rodriguez, Andreas Krause, Pietro Perona, Yisong Yue, Adish Singla
2018	J	`jnl`	A Moral Framework for Understanding of Fair ML through Economic Models of Equality of Opportunity. CoRR Hoda Heidari, Michele Loi, Krishna P. Gummadi, Andreas Krause
2018	—	`conf`	An Online Learning Approach to Generative Adversarial Networks. ICLR (Poster) Paulina Grnarova, Kfir Y. Levy, Aurélien Lucchi, Thomas Hofmann, Andreas Krause
2018	A*	`conf`	Differentiable Submodular Maximization. IJCAI Sebastian Tschiatschek, Aytunc Sahin, Andreas Krause
2018	J	`jnl`	Differentiable Submodular Maximization. CoRR Sebastian Tschiatschek, Aytunc Sahin, Andreas Krause
2018	A	`conf`	Discrete Sampling using Semigradient-based Product Mixtures. UAI Alkis Gotovos, S. Hamed Hassani, Andreas Krause, Stefanie Jegelka
2018	J	`jnl`	Discrete Sampling using Semigradient-based Product Mixtures. CoRR Alkis Gotovos, S. Hamed Hassani, Andreas Krause, Stefanie Jegelka
2018	A*	`conf`	Efficient High Dimensional Bayesian Optimization with Additivity and Quadrature Fourier Features. NeurIPS Mojmir Mutny, Andreas Krause
2018	J	`jnl`	Evaluating GANs via Duality. CoRR Paulina Grnarova, Kfir Y. Levy, Aurélien Lucchi, Nathanaël Perraudin, Thomas Hofmann, Andreas Krause
2018	A*	`conf`	Fairness Behind a Veil of Ignorance: A Welfare Analysis for Automated Decision Making. NeurIPS Hoda Heidari, Claudio Ferrari, Krishna P. Gummadi, Andreas Krause
2018	J	`jnl`	Fairness Behind a Veil of Ignorance: A Welfare Analysis for Automated Decision Making. CoRR Hoda Heidari, Claudio Ferrari, Krishna P. Gummadi, Andreas Krause
2018	—	`conf`	Fake News Detection in Social Networks via Crowd Signals. WWW (Companion Volume) Sebastian Tschiatschek, Adish Singla, Manuel Gomez-Rodriguez, Arpit Merchant, Andreas Krause
2018	J	`jnl`	Fast Gaussian Process Based Gradient Matching for Parameter Identification in Systems of Nonlinear ODEs. CoRR Philippe Wenk, Alkis Gotovos, Stefan Bauer, Nico S. Gorbach, Andreas Krause, Joachim M. Buhmann
2018	J	`jnl`	Generalization and Search in Risky Environments. Cogn. Sci. Eric Schulz, Charley M. Wu, Quentin J. M. Huys, Andreas Krause, Maarten Speekenbrink
2018	A*	`conf`	Incentive-Compatible Forecasting Competitions. AAAI Jens Witkowski, Rupert Freeman, Jennifer Wortman Vaughan, David M. Pennock, Andreas Krause
2018	A*	`conf`	Information Directed Sampling and Bandits with Heteroscedastic Noise. COLT Johannes Kirschner, Andreas Krause
2018	A*	`conf`	Information Gathering With Peers: Submodular Optimization With Peer-Prediction Constraints. AAAI Goran Radanovic, Adish Singla, Andreas Krause, Boi Faltings
2018	J	`jnl`	Information-Directed Exploration for Deep Reinforcement Learning. CoRR Nikolay Nikolov, Johannes Kirschner, Felix Berkenkamp, Andreas Krause
2018	A*	`conf`	Learning User Preferences to Incentivize Exploration in the Sharing Economy. AAAI Christoph Hirnschall, Adish Singla, Sebastian Tschiatschek, Andreas Krause
2018	J	`jnl`	Learning to Compensate Photovoltaic Power Fluctuations from Images of the Sky by Imitating an Optimal Policy. CoRR Robin Spiess, Felix Berkenkamp, Jan Poland, Andreas Krause
2018	A*	`conf`	Learning to Interact With Learning Agents. AAAI Adish Singla, Seyed Hamed Hassani, Andreas Krause
2018	—	`conf`	Learning-Based Model Predictive Control for Safe Exploration. CDC Torsten Koller, Felix Berkenkamp, Matteo Turchetta, Andreas Krause
2018	J	`jnl`	Learning-based Model Predictive Control for Safe Exploration and Reinforcement Learning. CoRR Torsten Koller, Felix Berkenkamp, Matteo Turchetta, Andreas Krause
2018	A*	`conf`	Online Variance Reduction for Stochastic Optimization. COLT Zalan Borsos, Andreas Krause, Kfir Y. Levy
2018	J	`jnl`	Online Variance Reduction for Stochastic Optimization. CoRR Zalán Borsos, Andreas Krause, Kfir Y. Levy
2018	J	`jnl`	Optimal DR-Submodular Maximization and Applications to Provable Mean Field Inference. CoRR An Bian, Joachim M. Buhmann, Andreas Krause
2018	A*	`conf`	Preventing Disparate Treatment in Sequential Decision Making. IJCAI Hoda Heidari, Andreas Krause
2018	A*	`ed.`	Proceedings of the 35th International Conference on Machine Learning, ICML 2018, Stockholmsmässan, Stockholm, Sweden, July 10-15, 2018 ICML Jennifer G. Dy, Andreas Krause
2018	A*	`conf`	Provable Variational Inference for Constrained Log-Submodular Models. NeurIPS Josip Djolonga, Stefanie Jegelka, Andreas Krause
2018	J	`jnl`	Reinforced Imitation: Sample Efficient Deep Reinforcement Learning for Map-less Navigation by Leveraging Prior Demonstrations. CoRR Mark Pfeiffer, Samarth Shukla, Matteo Turchetta, Cesar Cadena, Andreas Krause, Roland Siegwart, Juan I. Nieto
2018	J	`jnl`	Reinforced Imitation: Sample Efficient Deep Reinforcement Learning for Mapless Navigation by Leveraging Prior Demonstrations. IEEE Robotics Autom. Lett. Mark Pfeiffer, Samarth Shukla, Matteo Turchetta, Cesar Cadena, Andreas Krause, Roland Siegwart, Juan I. Nieto
2018	A*	`conf`	Scalable k -Means Clustering via Lightweight Coresets. KDD Olivier Bachem, Mario Lucic, Andreas Krause
2018	A*	`conf`	Streaming Non-Monotone Submodular Maximization: Personalized Video Summarization on the Fly. AAAI Baharan Mirzasoleiman, Stefanie Jegelka, Andreas Krause
2018	A	`conf`	Submodularity on Hypergraphs: From Sets to Sequences. AISTATS Marko Mitrovic, Moran Feldman, Andreas Krause, Amin Karbasi
2018	J	`jnl`	Submodularity on Hypergraphs: From Sets to Sequences. CoRR Marko Mitrovic, Moran Feldman, Andreas Krause, Amin Karbasi
2018	J	`jnl`	Teaching Multiple Concepts to Forgetful Learners. CoRR Anette Hunziker, Yuxin Chen, Oisin Mac Aodha, Manuel Gomez-Rodriguez, Andreas Krause, Pietro Perona, Yisong Yue, Adish Singla
2018	J	`jnl`	The Lyapunov Neural Network: Adaptive Stability Certification for Safe Learning of Dynamic Systems. CoRR Spencer M. Richards, Felix Berkenkamp, Andreas Krause
2018	Misc	`conf`	The Lyapunov Neural Network: Adaptive Stability Certification for Safe Learning of Dynamical Systems. CoRL Spencer M. Richards, Felix Berkenkamp, Andreas Krause
2018	J	`jnl`	Unsupervised Imitation Learning. CoRR Sebastian Curi, Kfir Y. Levy, Andreas Krause
2017	J	`jnl`	An Online Learning Approach to Generative Adversarial Networks. CoRR Paulina Grnarova, Kfir Y. Levy, Aurélien Lucchi, Thomas Hofmann, Andreas Krause
2017	J	`jnl`	Coordinated Online Learning With Applications to Learning User Preferences. CoRR Christoph Hirnschall, Adish Singla, Sebastian Tschiatschek, Andreas Krause
2017	A*	`conf`	Deletion-Robust Submodular Maximization: Data Summarization with "the Right to be Forgotten". ICML Baharan Mirzasoleiman, Amin Karbasi, Andreas Krause
2017	J	`jnl`	Detecting Fake News in Social Networks via Crowdsourcing. CoRR Sebastian Tschiatschek, Adish Singla, Manuel Gomez-Rodriguez, Arpit Merchant, Andreas Krause
2017	—	`conf`	Differentiable Learning of Submodular Functions. NIPS Josip Djolonga, Andreas Krause
2017	A*	`conf`	Differentially Private Submodular Maximization: Data Summarization in Disguise. ICML Marko Mitrovic, Mark Bun, Andreas Krause, Amin Karbasi
2017	A*	`conf`	Distributed and Provably Good Seedings for k-Means in Constant Rounds. ICML Olivier Bachem, Mario Lucic, Andreas Krause
2017	A	`conf`	Efficient Online Learning for Optimizing Value of Information: Theory and Application to Interactive Troubleshooting. UAI Yuxin Chen, Jean-Michel Renders, Morteza Haghir Chehreghani, Andreas Krause
2017	J	`jnl`	Efficient Online Learning for Optimizing Value of Information: Theory and Application to Interactive Troubleshooting. CoRR Yuxin Chen, Jean-Michel Renders, Morteza Haghir Chehreghani, Andreas Krause
2017	A	`conf`	Guaranteed Non-convex Optimization: Submodular Maximization over Continuous Domains. AISTATS Andrew An Bian, Baharan Mirzasoleiman, Joachim M. Buhmann, Andreas Krause
2017	A*	`conf`	Guarantees for Greedy Maximization of Non-submodular Functions with Applications. ICML Andrew An Bian, Joachim M. Buhmann, Andreas Krause, Sebastian Tschiatschek
2017	J	`jnl`	Guarantees for Greedy Maximization of Non-submodular Functions with Applications. CoRR Andrew An Bian, Joachim M. Buhmann, Andreas Krause, Sebastian Tschiatschek
2017	A	`conf`	Improving Optimization-Based Approximate Inference by Clamping Variables. UAI Junyao Zhao, Josip Djolonga, Sebastian Tschiatschek, Andreas Krause
2017	J	`jnl`	Information Gathering with Peers: Submodular Optimization with Peer-Prediction Constraints. CoRR Goran Radanovic, Adish Singla, Andreas Krause, Boi Faltings
2017	—	`conf`	Interactive Submodular Bandit. NIPS Lin Chen, Andreas Krause, Amin Karbasi
2017	J	`jnl`	Learning Implicit Generative Models Using Differentiable Graph Tests. CoRR Josip Djolonga, Andreas Krause
2017	J	`jnl`	Learning User Preferences to Incentivize Exploration in the Sharing Economy. CoRR Christoph Hirnschall, Adish Singla, Sebastian Tschiatschek, Andreas Krause
2017	J	`jnl`	Learning to Use Learners' Advice. CoRR Adish Singla, Seyed Hamed Hassani, Andreas Krause
2017	J	`jnl`	Machine Learning and Formal Method (Dagstuhl Seminar 17351). Dagstuhl Reports Sanjit A. Seshia, Xiaojin (Jerry) Zhu, Andreas Krause, Susmit Jha
2017	A	`conf`	Near-optimal Bayesian Active Learning with Correlated and Noisy Tests. AISTATS Yuxin Chen, Seyed Hamed Hassani, Andreas Krause
2017	—	`conf`	Non-monotone Continuous DR-submodular Maximization: Structure and Algorithms. NIPS An Bian, Kfir Yehuda Levy, Andreas Krause, Joachim M. Buhmann
2017	J	`jnl`	Non-monotone Continuous DR-submodular Maximization: Structure and Algorithms. CoRR An Bian, Kfir Y. Levy, Andreas Krause, Joachim M. Buhmann
2017	A*	`conf`	Probabilistic Submodular Maximization in Sub-Linear Time. ICML Serban Stan, Morteza Zadimoghaddam, Andreas Krause, Amin Karbasi
2017	A*	`conf`	Proper Proxy Scoring Rules. AAAI Jens Witkowski, Pavel Atanasov, Lyle H. Ungar, Andreas Krause
2017	—	`conf`	Safe Model-based Reinforcement Learning with Stability Guarantees. NIPS Felix Berkenkamp, Matteo Turchetta, Angela P. Schoellig, Andreas Krause
2017	J	`jnl`	Safe Model-based Reinforcement Learning with Stability Guarantees. CoRR Felix Berkenkamp, Matteo Turchetta, Angela P. Schoellig, Andreas Krause
2017	J	`jnl`	Scalable and Distributed Clustering via Lightweight Coresets. CoRR Olivier Bachem, Mario Lucic, Andreas Krause
2017	A*	`conf`	Selecting Sequences of Items via Submodular Maximization. AAAI Sebastian Tschiatschek, Adish Singla, Andreas Krause
2017	—	`conf`	Stochastic Submodular Maximization: The Case of Coverage Functions. NIPS Mohammad Reza Karimi, Mario Lucic, S. Hamed Hassani, Andreas Krause
2017	J	`jnl`	Stochastic Submodular Maximization: The Case of Coverage Functions. CoRR Mohammad Reza Karimi, Mario Lucic, S. Hamed Hassani, Andreas Krause
2017	J	`jnl`	Streaming Non-monotone Submodular Maximization: Personalized Video Summarization on the Fly. CoRR Baharan Mirzasoleiman, Stefanie Jegelka, Andreas Krause
2017	J	`jnl`	Training Gaussian Mixture Models at Scale via Coresets. J. Mach. Learn. Res. Mario Lucic, Matthew Faulkner, Andreas Krause, Dan Feldman
2017	J	`jnl`	Uniform Deviation Bounds for Unbounded Loss Functions like k-Means. CoRR Olivier Bachem, Mario Lucic, S. Hamed Hassani, Andreas Krause
2017	A*	`conf`	Uniform Deviation Bounds for k-Means Clustering. ICML Olivier Bachem, Mario Lucic, S. Hamed Hassani, Andreas Krause
2017	J	`jnl`	Virtual vs. Real: Trading Off Simulations and Physical Experiments in Reinforcement Learning with Bayesian Optimization. CoRR Alonso Marco, Felix Berkenkamp, Philipp Hennig, Angela P. Schoellig, Andreas Krause, Stefan Schaal, Sebastian Trimpe
2017	A*	`conf`	Virtual vs. real: Trading off simulations and physical experiments in reinforcement learning with Bayesian optimization. ICRA Alonso Marco, Felix Berkenkamp, Philipp Hennig, Angela P. Schoellig, Andreas Krause, Stefan Schaal, Sebastian Trimpe
2016	A*	`conf`	Actively Learning Hemimetrics with Applications to Eliciting User Preferences. ICML Adish Singla, Sebastian Tschiatschek, Andreas Krause
2016	J	`jnl`	Actively Learning Hemimetrics with Applications to Eliciting User Preferences. CoRR Adish Singla, Sebastian Tschiatschek, Andreas Krause
2016	J	`jnl`	Algorithms for Learning Sparse Additive Models with Interactions in High Dimensions. CoRR Hemant Tyagi, Anastasios Kyrillidis, Bernd Gärtner, Andreas Krause
2016	A*	`conf`	Approximate K-Means++ in Sublinear Time. AAAI Olivier Bachem, Mario Lucic, S. Hamed Hassani, Andreas Krause
2016	J	`jnl`	Bayesian Optimization with Safety Constraints: Safe and Automatic Parameter Tuning in Robotics. CoRR Felix Berkenkamp, Andreas Krause, Angela P. Schoellig
2016	—	`conf`	Bayesian optimization for maximum power point tracking in photovoltaic power plants. ECC Hany Abdelrahman, Felix Berkenkamp, Jan Poland, Andreas Krause
2016	B	`conf`	Better safe than sorry: Risky function exploitation through safe optimization. CogSci Eric Schulz, Quentin J. M. Huys, Dominik R. Bach, Maarten Speekenbrink, Andreas Krause
2016	J	`jnl`	Better safe than sorry: Risky function exploitation through safe optimization. CoRR Eric Schulz, Quentin J. M. Huys, Dominik R. Bach, Maarten Speekenbrink, Andreas Krause
2016	—	`conf`	Cooperative Graphical Models. NIPS Josip Djolonga, Stefanie Jegelka, Sebastian Tschiatschek, Andreas Krause
2016	J	`jnl`	Distributed Submodular Maximization. J. Mach. Learn. Res. Baharan Mirzasoleiman, Amin Karbasi, Rik Sarkar, Andreas Krause
2016	B	`conf`	Evaluating Task-Dependent Taxonomies for Navigation. HCOMP Yuyin Sun, Adish Singla, Tori Qiao Yan, Andreas Krause, Dieter Fox
2016	—	`conf`	Fast and Provably Good Seedings for k-Means. NIPS Olivier Bachem, Mario Lucic, Seyed Hamed Hassani, Andreas Krause
2016	J	`jnl`	Guaranteed Non-convex Optimization: Submodular Maximization over Continuous Domains. CoRR Andrew An Bian, Baharan Mirzasoleiman, Joachim M. Buhmann, Andreas Krause
2016	A*	`conf`	Horizontally Scalable Submodular Maximization. ICML Mario Lucic, Olivier Bachem, Morteza Zadimoghaddam, Andreas Krause
2016	J	`jnl`	Horizontally Scalable Submodular Maximization. CoRR Mario Lucic, Olivier Bachem, Morteza Zadimoghaddam, Andreas Krause
2016	A	`conf`	Learning Probabilistic Submodular Diversity Models Via Noise Contrastive Estimation. AISTATS Sebastian Tschiatschek, Josip Djolonga, Andreas Krause
2016	A	`conf`	Learning Sparse Additive Models with Interactions in High Dimensions. AISTATS Hemant Tyagi, Anastasios Kyrillidis, Bernd Gärtner, Andreas Krause
2016	J	`jnl`	Learning Sparse Additive Models with Interactions in High Dimensions. CoRR Hemant Tyagi, Anastasios Kyrillidis, Bernd Gärtner, Andreas Krause
2016	A*	`conf`	Learning Sparse Combinatorial Representations via Two-stage Submodular Maximization. ICML Eric Balkanski, Baharan Mirzasoleiman, Andreas Krause, Yaron Singer
2016	B	`conf`	Learning and Feature Selection under Budget Constraints in Crowdsourcing. HCOMP Besmira Nushi, Adish Singla, Andreas Krause, Donald Kossmann
2016	A*	`conf`	Learning programs from noisy data. POPL Veselin Raychev, Pavol Bielik, Martin T. Vechev, Andreas Krause
2016	A*	`conf`	Linear-Time Outlier Detection via Sensitivity. IJCAI Mario Lucic, Olivier Bachem, Andreas Krause
2016	J	`jnl`	Linear-time Outlier Detection via Sensitivity. CoRR Mario Lucic, Olivier Bachem, Andreas Krause
2016	J	`jnl`	Near-optimal Bayesian Active Learning with Correlated and Noisy Tests. CoRR Yuxin Chen, S. Hamed Hassani, Andreas Krause
2016	A*	`conf`	Noisy Submodular Maximization via Adaptive Sampling with Applications to Crowdsourced Image Collection Summarization. AAAI Adish Singla, Sebastian Tschiatschek, Andreas Krause
2016	—	`conf`	Safe Exploration in Finite Markov Decision Processes with Gaussian Processes. NIPS Matteo Turchetta, Felix Berkenkamp, Andreas Krause
2016	J	`jnl`	Safe Exploration in Finite Markov Decision Processes with Gaussian Processes. CoRR Matteo Turchetta, Felix Berkenkamp, Andreas Krause
2016	J	`jnl`	Safe Learning of Regions of Attraction for Uncertain, Nonlinear Systems with Gaussian Processes. CoRR Felix Berkenkamp, Riccardo Moriconi, Angela P. Schoellig, Andreas Krause
2016	A*	`conf`	Safe controller optimization for quadrotors with Gaussian processes. ICRA Felix Berkenkamp, Angela P. Schoellig, Andreas Krause
2016	—	`conf`	Safe learning of regions of attraction for uncertain, nonlinear systems with Gaussian processes. CDC Felix Berkenkamp, Riccardo Moriconi, Angela P. Schoellig, Andreas Krause
2016	A	`conf`	Strong Coresets for Hard and Soft Bregman Clustering with Applications to Exponential Family Mixtures. AISTATS Mario Lucic, Olivier Bachem, Andreas Krause
2016	—	`conf`	Suggesting Sounds for Images from Video Collections. ECCV Workshops (2) Matthias Solèr, Jean-Charles Bazin, Oliver Wang, Andreas Krause, Alexander Sorkine-Hornung
2016	J	`jnl`	Tradeoffs for Space, Time, Data and Risk in Unsupervised Learning. CoRR Mario Lucic, Mesrob I. Ohannessian, Amin Karbasi, Andreas Krause
2016	—	`conf`	Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation. NIPS Ilija Bogunovic, Jonathan Scarlett, Andreas Krause, Volkan Cevher
2016	J	`jnl`	Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation. CoRR Ilija Bogunovic, Jonathan Scarlett, Andreas Krause, Volkan Cevher
2016	—	`conf`	Variational Inference in Mixed Probabilistic Submodular Models. NIPS Josip Djolonga, Sebastian Tschiatschek, Andreas Krause
2016	J	`jnl`	e-PAL: An Active Learning Approach to the Multi-Objective Optimization Problem. J. Mach. Learn. Res. Marcela Zuluaga, Andreas Krause, Markus Püschel
2015	A*	`conf`	Building Hierarchies of Concepts via Crowdsourcing. IJCAI Yuyin Sun, Adish Singla, Dieter Fox, Andreas Krause
2015	J	`jnl`	Building Hierarchies of Concepts via Crowdsourcing. CoRR Yuyin Sun, Adish Singla, Dieter Fox, Andreas Krause
2015	A*	`conf`	Coresets for Nonparametric Estimation - the Case of DP-Means. ICML Olivier Bachem, Mario Lucic, Andreas Krause
2015	B	`conf`	Crowd Access Path Optimization: Diversity Matters. HCOMP Besmira Nushi, Adish Singla, Anja Gruenheid, Erfan Zamanian, Andreas Krause, Donald Kossmann
2015	J	`jnl`	Crowd Access Path Optimization: Diversity Matters. CoRR Besmira Nushi, Adish Singla, Anja Gruenheid, Erfan Zamanian, Andreas Krause, Donald Kossmann
2015	J	`jnl`	Discovering Valuable Items from Massive Data. CoRR Hastagiri P. Vanchinathan, Andreas Marfurt, Charles-Antoine Robelin, Donald Kossmann, Andreas Krause
2015	A*	`conf`	Discovering Valuable items from Massive Data. KDD Hastagiri P. Vanchinathan, Andreas Marfurt, Charles-Antoine Robelin, Donald Kossmann, Andreas Krause
2015	—	`conf`	Distributed Submodular Cover: Succinctly Summarizing Massive Data. NIPS Baharan Mirzasoleiman, Amin Karbasi, Ashwinkumar Badanidiyuru, Andreas Krause
2015	A*	`conf`	Efficient visual exploration and coverage with a micro aerial vehicle in unknown environments. ICRA Lionel Heng, Alkis Gotovos, Andreas Krause, Marc Pollefeys
2015	A*	`conf`	Higher-Order Inference for Multi-class Log-Supermodular Models. ICCV Jian Zhang, Josip Djolonga, Andreas Krause
2015	A*	`conf`	Incentivizing Users for Balancing Bike Sharing Systems. AAAI Adish Singla, Marco Santoni, Gábor Bartók, Pratik Mukerji, Moritz Meenen, Andreas Krause
2015	A*	`conf`	Information Gathering in Networks via Active Exploration. IJCAI Adish Singla, Eric Horvitz, Pushmeet Kohli, Ryen White, Andreas Krause
2015	J	`jnl`	Information Gathering in Networks via Active Exploration. CoRR Adish Singla, Eric Horvitz, Pushmeet Kohli, Ryen W. White, Andreas Krause
2015	A*	`conf`	Lazier Than Lazy Greedy. AAAI Baharan Mirzasoleiman, Ashwinkumar Badanidiyuru, Amin Karbasi, Jan Vondrák, Andreas Krause
2015	B	`conf`	Learning to Hire Teams. HCOMP Adish Singla, Eric Horvitz, Pushmeet Kohli, Andreas Krause
2015	J	`jnl`	Learning to Hire Teams. CoRR Adish Singla, Eric Horvitz, Pushmeet Kohli, Andreas Krause
2015	J	`jnl`	Noisy Submodular Maximization via Adaptive Sampling with Applications to Crowdsourced Image Collection Summarization. CoRR Adish Singla, Sebastian Tschiatschek, Andreas Krause
2015	A*	`conf`	Non-Monotone Adaptive Submodular Maximization. IJCAI Alkis Gotovos, Amin Karbasi, Andreas Krause
2015	A*	`conf`	Predicting Program Properties from "Big Code". POPL Veselin Raychev, Martin T. Vechev, Andreas Krause
2015	J	`jnl`	Robot navigation in dense human crowds: Statistical models and experimental studies of human-robot cooperation. Int. J. Robotics Res. Peter Trautman, Jeremy Ma, Richard M. Murray, Andreas Krause
2015	J	`jnl`	Safe Controller Optimization for Quadrotors with Gaussian Processes. CoRR Felix Berkenkamp, Angela P. Schoellig, Andreas Krause
2015	A*	`conf`	Safe Exploration for Optimization with Gaussian Processes. ICML Yanan Sui, Alkis Gotovos, Joel W. Burdick, Andreas Krause
2015	—	`conf`	Sampling from Probabilistic Submodular Models. NIPS Alkis Gotovos, S. Hamed Hassani, Andreas Krause
2015	A*	`conf`	Scalable Variational Inference in Log-supermodular Models. ICML Josip Djolonga, Andreas Krause
2015	J	`jnl`	Scalable Variational Inference in Log-supermodular Models. CoRR Josip Djolonga, Andreas Krause
2015	A*	`conf`	Sequential Information Maximization: When is Greedy Near-optimal? COLT Yuxin Chen, S. Hamed Hassani, Amin Karbasi, Andreas Krause
2015	J	`jnl`	Strong Coresets for Hard and Soft Bregman Clustering with Applications to Exponential Family Mixtures. CoRR Mario Lucic, Olivier Bachem, Andreas Krause
2015	A*	`conf`	Submodular Surrogates for Value of Information. AAAI Yuxin Chen, Shervin Javdani, Amin Karbasi, J. Andrew Bagnell, Siddhartha S. Srinivasa, Andreas Krause
2015	A	`conf`	Tradeoffs for Space, Time, Data and Risk in Unsupervised Learning. AISTATS Mario Lucic, Mesrob I. Ohannessian, Amin Karbasi, Andreas Krause
2014	J	`jnl`	A Utility-Theoretic Approach to Privacy in Online Services. CoRR Andreas Krause, Eric Horvitz
2014	A*	`conf`	Active Detection via Adaptive Submodularity. ICML Yuxin Chen, Hiroaki Shioi, Cesar Fuentes Montesinos, Lian Pin Koh, Serge A. Wich, Andreas Krause
2014	J	`jnl`	Community sense and response systems: your phone as quake detector. Commun. ACM Matthew Faulkner, Robert Clayton, Thomas Heaton, K. Mani Chandy, Monica D. Kohler, Julian J. Bunn, Richard Guy, Annie H. Liu, Michael Olson, MingHei Cheng, Andreas Krause
2014	—	`conf`	Community sense-and-response systems: Your phone as seismometer. PerCom Workshops Andreas Krause
2014	B	`conf`	Contextual Procurement in Online Crowdsourcing Markets. HCOMP Adish Singla, Ian Lienert, Gábor Bartók, Andreas Krause
2014	J	`jnl`	Distributed Submodular Maximization. CoRR Baharan Mirzasoleiman, Amin Karbasi, Rik Sarkar, Andreas Krause
2014	J	`jnl`	Efficient Informative Sensing using Multiple Robots. CoRR Amarjeet Singh, Andreas Krause, Carlos Guestrin, William J. Kaiser
2014	—	`conf`	Efficient Partial Monitoring with Prior Information. NIPS Hastagiri P. Vanchinathan, Gábor Bartók, Andreas Krause
2014	—	`conf`	Efficient Sampling for Learning Sparse Additive Models in High Dimensions. NIPS Hemant Tyagi, Bernd Gärtner, Andreas Krause
2014	A	`conf`	Explore-exploit in top-N recommender systems via Gaussian processes. RecSys Hastagiri P. Vanchinathan, Isidor Nikolic, Fabio De Bona, Andreas Krause
2014	—	`conf`	From MAP to Marginals: Variational Inference in Bayesian Submodular Models. NIPS Josip Djolonga, Andreas Krause
2014	A*	`conf`	Fully autonomous focused exploration for robotic environmental monitoring. ICRA Gregory Hitz, Alkis Gotovos, François Pomerleau, Marie-Eve Garneau, Cédric Pradalier, Andreas Krause, Roland Yves Siegwart
2014	J	`jnl`	Lazier Than Lazy Greedy. CoRR Baharan Mirzasoleiman, Ashwinkumar Badanidiyuru, Amin Karbasi, Jan Vondrák, Andreas Krause
2014	A	`conf`	Near Optimal Bayesian Active Learning for Decision Making. AISTATS Shervin Javdani, Yuxin Chen, Amin Karbasi, Andreas Krause, Drew Bagnell, Siddhartha S. Srinivasa
2014	J	`jnl`	Near Optimal Bayesian Active Learning for Decision Making. CoRR Shervin Javdani, Yuxin Chen, Amin Karbasi, Andreas Krause, J. Andrew Bagnell, Siddhartha S. Srinivasa
2014	A*	`conf`	Near-Optimally Teaching the Crowd to Classify. ICML Adish Singla, Ilija Bogunovic, Gábor Bartók, Amin Karbasi, Andreas Krause
2014	J	`jnl`	Near-Optimally Teaching the Crowd to Classify. CoRR Adish Singla, Ilija Bogunovic, Gábor Bartók, Amin Karbasi, Andreas Krause
2014	J	`jnl`	Online Submodular Maximization under a Matroid Constraint with Application to Learning Assignments. CoRR Daniel Golovin, Andreas Krause, Matthew J. Streeter
2014	J	`jnl`	Optimal Value of Information in Graphical Models. CoRR Andreas Krause, Carlos Guestrin
2014	J	`jnl`	Parallelizing exploration-exploitation tradeoffs in Gaussian process bandit optimization. J. Mach. Learn. Res. Thomas Desautels, Andreas Krause, Joel W. Burdick
2014	J	`jnl`	Sequential Decision Making in Computational Sustainability via Adaptive Submodularity. AI Mag. Andreas Krause, Daniel Golovin, Sarah J. Converse
2014	A*	`conf`	Streaming submodular maximization: massive data summarization on the fly. KDD Ashwinkumar Badanidiyuru, Baharan Mirzasoleiman, Amin Karbasi, Andreas Krause
2014	—	`ch.`	Submodular Function Maximization. Tractability Andreas Krause, Daniel Golovin
2013	—	`conf`	A fresh perspective: learning to sparsify for detection in massive noisy sensor networks. IPSN Matthew Faulkner, Annie H. Liu, Andreas Krause
2013	A*	`conf`	Active Learning for Level Set Estimation. IJCAI Alkis Gotovos, Nathalie Casati, Gregory Hitz, Andreas Krause
2013	—	`conf`	Active Learning for Multi-Objective Optimization. ICML (1) Marcela Zuluaga, Guillaume Sergent, Andreas Krause, Markus Püschel
2013	—	`conf`	Distributed Submodular Maximization: Identifying Representative Elements in Massive Data. NIPS Baharan Mirzasoleiman, Amin Karbasi, Rik Sarkar, Andreas Krause
2013	—	`conf`	High-Dimensional Gaussian Process Bandits. NIPS Josip Djolonga, Andreas Krause, Volkan Cevher
2013	B	`conf`	Incentives for Privacy Tradeoff in Community Sensing. HCOMP Adish Singla, Andreas Krause
2013	J	`jnl`	Incentives for Privacy Tradeoff in Community Sensing. CoRR Adish Singla, Andreas Krause
2013	J	`jnl`	Navigating the protein fitness landscape with Gaussian processes. Proc. Natl. Acad. Sci. USA Philip A. Romero, Andreas Krause, Frances H. Arnold
2013	—	`conf`	Near-optimal Batch Mode Active Learning and Adaptive Submodular Optimization. ICML (1) Yuxin Chen, Andreas Krause
2013	J	`jnl`	Optimizing waypoints for monitoring spatiotemporal phenomena. Int. J. Robotics Res. Jonathan Binney, Andreas Krause, Gaurav S. Sukhatme
2013	A*	`conf`	Robot navigation in dense human crowds: the case for cooperation. ICRA Peter Trautman, Jeremy Ma, Richard M. Murray, Andreas Krause
2013	A	`conf`	Robust landmark selection for mobile robot navigation. IROS Maximilian Beinhofer, Jörg Müller, Andreas Krause, Wolfram Burgard
2013	A	`conf`	Submodularity in Machine Learning and Vision. BMVC Andreas Krause
2013	J	`jnl`	Towards a living earth simulator CoRR Mario Paolucci, Donald Kossmann, Rosaria Conte, Paul Lukowicz, Panos Argyrakis, Ann Blandford, Giulia Bonelli, Stuart Anderson, Sara de Freitas, Bruce Edmonds, Nigel Gilbert, Markus H. Gross, Jörn Kohlhammer, Petros Koumoutsakos, Andreas Krause, Björn-Ola Linnér, Philipp Slusallek, Olga Sorkine, Robert W. Sumner, Dirk Helbing
2013	A*	`conf`	Truthful incentives in crowdsourcing tasks using regret minimization mechanisms. WWW Adish Singla, Andreas Krause
2012	B	`conf`	"Smart" design space sampling to predict Pareto-optimal solutions. LCTES Marcela Zuluaga, Andreas Krause, Peter A. Milder, Markus Püschel
2012	J	`jnl`	Inferring Networks of Diffusion and Influence. ACM Trans. Knowl. Discov. Data Manuel Gomez-Rodriguez, Jure Leskovec, Andreas Krause
2012	J	`jnl`	Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting. IEEE Trans. Inf. Theory Niranjan Srinivas, Andreas Krause, Sham M. Kakade, Matthias W. Seeger
2012	A*	`conf`	Joint Optimization and Variable Selection of High-dimensional Gaussian Processes. ICML Bo Chen, Rui M. Castro, Andreas Krause
2012	A	`conf`	Learning Fourier Sparse Set Functions. AISTATS Peter Stobbe, Andreas Krause
2012	J	`jnl`	Near-optimal Nonmyopic Value of Information in Graphical Models CoRR Andreas Krause, Carlos Guestrin
2012	A*	`conf`	Parallelizing Exploration-Exploitation Tradeoffs with Gaussian Process Bandit Optimization. ICML Thomas Desautels, Andreas Krause, Joel W. Burdick
2011	J	`jnl`	Adaptive Submodular Optimization under Matroid Constraints CoRR Daniel Golovin, Andreas Krause
2011	J	`jnl`	Adaptive Submodularity: Theory and Applications in Active Learning and Stochastic Optimization. J. Artif. Intell. Res. Daniel Golovin, Andreas Krause
2011	—	`conf`	Contextual Gaussian Process Bandit Optimization. NIPS Andreas Krause, Cheng Soon Ong
2011	—	`conf`	Crowdclustering. NIPS Ryan Gomes, Peter Welinder, Andreas Krause, Pietro Perona
2011	—	`conf`	Demo abstract, the next big one: Detecting earthquakes and other rare events from community-based sensors. IPSN Matthew Faulkner, Michael Olson, Rishi Chandy, Jonathan Krause, K. Mani Chandy, Andreas Krause
2011	A*	`conf`	Dynamic Resource Allocation in Conservation Planning. AAAI Daniel Golovin, Andreas Krause, Beth Gardner, Sarah J. Converse, Steve Morey
2011	J	`jnl`	Greedy Dictionary Selection for Sparse Representation. IEEE J. Sel. Top. Signal Process. Volkan Cevher, Andreas Krause
2011	A*	`conf`	Randomized Sensing in Adversarial Environments. IJCAI Andreas Krause, Alex Roper, Daniel Golovin
2011	J	`jnl`	Robust sensor placements at informative and communication-efficient locations. ACM Trans. Sens. Networks Andreas Krause, Carlos Guestrin, Anupam Gupta, Jon M. Kleinberg
2011	—	`conf`	Scalable Training of Mixture Models via Coresets. NIPS Dan Feldman, Matthew Faulkner, Andreas Krause
2011	J	`jnl`	Simultaneous Optimization of Sensor Placements and Balanced Schedules. IEEE Trans. Autom. Control. Andreas Krause, Ram Rajagopal, Anupam Gupta, Carlos Guestrin
2011	J	`jnl`	Submodularity and its applications in optimized information gathering. ACM Trans. Intell. Syst. Technol. Andreas Krause, Carlos Guestrin
2011	—	`conf`	The next big one: Detecting earthquakes and other rare events from community-based sensors. IPSN Matthew Faulkner, Michael Olson, Rishi Chandy, Jonathan Krause, K. Mani Chandy, Andreas Krause
2010	J	`jnl`	A Utility-Theoretic Approach to Privacy in Online Services. J. Artif. Intell. Res. Andreas Krause, Eric Horvitz
2010	J	`jnl`	Adaptive Submodularity: A New Approach to Active Learning and Stochastic Optimization CoRR Daniel Golovin, Andreas Krause
2010	A*	`conf`	Adaptive Submodularity: A New Approach to Active Learning and Stochastic Optimization. COLT Daniel Golovin, Andreas Krause
2010	A*	`conf`	Budgeted Nonparametric Learning from Data Streams. ICML Ryan Gomes, Andreas Krause
2010	—	`conf`	Discriminative Clustering by Regularized Information Maximization. NIPS Ryan Gomes, Andreas Krause, Pietro Perona
2010	J	`jnl`	Efficient Minimization of Decomposable Submodular Functions CoRR Peter Stobbe, Andreas Krause
2010	—	`conf`	Efficient Minimization of Decomposable Submodular Functions. NIPS Peter Stobbe, Andreas Krause
2010	A*	`conf`	Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design. ICML Niranjan Srinivas, Andreas Krause, Sham M. Kakade, Matthias W. Seeger
2010	J	`jnl`	Inferring Networks of Diffusion and Influence CoRR Manuel Gomez-Rodriguez, Jure Leskovec, Andreas Krause
2010	A*	`conf`	Inferring networks of diffusion and influence. KDD Manuel Gomez-Rodriguez, Jure Leskovec, Andreas Krause
2010	A*	`conf`	Informative path planning for an autonomous underwater vehicle. ICRA Jonathan Binney, Andreas Krause, Gaurav S. Sukhatme
2010	J	`jnl`	Near-Optimal Bayesian Active Learning with Noisy Observations CoRR Daniel Golovin, Andreas Krause, Debajyoti Ray
2010	—	`conf`	Near-Optimal Bayesian Active Learning with Noisy Observations. NIPS Daniel Golovin, Andreas Krause, Debajyoti Ray
2010	J	`jnl`	Online Distributed Sensor Selection CoRR Daniel Golovin, Matthew Faulkner, Andreas Krause
2010	—	`conf`	Online distributed sensor selection. IPSN Daniel Golovin, Matthew Faulkner, Andreas Krause
2010	J	`jnl`	SFO: A Toolbox for Submodular Function Optimization. J. Mach. Learn. Res. Andreas Krause
2010	A*	`conf`	Submodular Dictionary Selection for Sparse Representation. ICML Andreas Krause, Volkan Cevher
2010	A	`conf`	Unfreezing the robot: Navigation in dense, interacting crowds. IROS Peter Trautman, Andreas Krause
2009	J	`jnl`	Efficient Informative Sensing using Multiple Robots. J. Artif. Intell. Res. Amarjeet Singh, Andreas Krause, Carlos Guestrin, William J. Kaiser
2009	J	`jnl`	Gaussian Process Bandits without Regret: An Experimental Design Approach CoRR Niranjan Srinivas, Andreas Krause, Sham M. Kakade, Matthias W. Seeger
2009	A*	`conf`	Nonmyopic Adaptive Informative Path Planning for Multiple Robots. IJCAI Amarjeet Singh, Andreas Krause, William J. Kaiser
2009	J	`jnl`	Online Learning of Assignments that Maximize Submodular Functions CoRR Daniel Golovin, Andreas Krause, Matthew J. Streeter
2009	—	`conf`	Online Learning of Assignments. NIPS Matthew J. Streeter, Daniel Golovin, Andreas Krause
2009	J	`jnl`	Optimal Value of Information in Graphical Models. J. Artif. Intell. Res. Andreas Krause, Carlos Guestrin
2009	J	`jnl`	Optimizing Sensing: From Water to the Web. Computer Andreas Krause, Carlos Guestrin
2009	—	`conf`	Simultaneous placement and scheduling of sensors. IPSN Andreas Krause, Ram Rajagopal, Anupam Gupta, Carlos Guestrin
2008	A*	`conf`	A Utility-Theoretic Approach to Privacy and Personalization. AAAI Andreas Krause, Eric Horvitz
2008	J	`jnl`	Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies. J. Mach. Learn. Res. Andreas Krause, Ajit Paul Singh, Carlos Guestrin
2008	—	`conf`	Toward Community Sensing. IPSN Andreas Krause, Eric Horvitz, Aman Kansal, Feng Zhao
2007	A*	`conf`	Cost-effective outbreak detection in networks. KDD Jure Leskovec, Andreas Krause, Carlos Guestrin, Christos Faloutsos, Jeanne M. VanBriesen, Natalie S. Glance
2007	A*	`conf`	Efficient Planning of Informative Paths for Multiple Robots. IJCAI Amarjeet Singh, Andreas Krause, Carlos Guestrin, William J. Kaiser, Maxim A. Batalin
2007	A*	`conf`	Near-optimal Observation Selection using Submodular Functions. AAAI Andreas Krause, Carlos Guestrin
2007	A*	`conf`	Nonmyopic Informative Path Planning in Spatio-Temporal Models. AAAI Alexandra Meliou, Andreas Krause, Carlos Guestrin, Joseph M. Hellerstein
2007	A*	`conf`	Nonmyopic active learning of Gaussian processes: an exploration-exploitation approach. ICML Andreas Krause, Carlos Guestrin
2007	A*	`conf`	Robust, low-cost, non-intrusive sensing and recognition of seated postures. UIST Bilge Mutlu, Andreas Krause, Jodi Forlizzi, Carlos Guestrin, Jessica K. Hodgins
2007	—	`conf`	Selecting Observations against Adversarial Objectives. NIPS Andreas Krause, H. Brendan McMahan, Carlos Guestrin, Anupam Gupta
2006	J	`jnl`	Context-Aware Mobile Computing: Learning Context-Dependent Personal Preferences from a Wearable Sensor Array. IEEE Trans. Mob. Comput. Andreas Krause, Asim Smailagic, Daniel P. Siewiorek
2006	A*	`conf`	Data association for topic intensity tracking. ICML Andreas Krause, Jure Leskovec, Carlos Guestrin
2006	—	`conf`	Near-optimal sensor placements: maximizing information while minimizing communication cost. IPSN Andreas Krause, Carlos Guestrin, Anupam Gupta, Jon M. Kleinberg
2005	Misc	`conf`	Intelligent light control using sensor networks. SenSys Vipul Singhvi, Andreas Krause, Carlos Guestrin, James H. Garrett Jr., H. Scott Matthews
2005	A	`conf`	Near-optimal Nonmyopic Value of Information in Graphical Models. UAI Andreas Krause, Carlos Guestrin
2005	A*	`conf`	Near-optimal sensor placements in Gaussian processes. ICML Carlos Guestrin, Andreas Krause, Ajit Paul Singh
2005	A*	`conf`	Optimal Nonmyopic Value of Information in Graphical Models - Efficient Algorithms and Theoretical Limits. IJCAI Andreas Krause, Carlos Guestrin
2005	Misc	`conf`	Trading off Prediction Accuracy and Power Consumption for Context-Aware Wearable Computing. ISWC Andreas Krause, Matthias Ihmig, Edward Rankin, Derek Leong, Smriti Gupta, Daniel P. Siewiorek, Asim Smailagic, Michael Deisher, Uttam Sengupta
2004	J	`jnl`	Development and implementation of a parallel algorithm for the fast design of oligonucleotide probe sets for diagnostic DNA microarrays. Concurr. Pract. Exp. Harald Meier, Andreas Krause, Markus Kräutner, Arndt Bode
2004	J	`jnl`	Mobile decision support for transplantation patient data. Int. J. Medical Informatics Andreas Krause, Dominik Hartl, Fabian J. Theis, Manfred Stangl, Klaus-E. Gerauer, Alexander T. Mehlhorn
2003	A	`conf`	Accurate Method for Fast Design of Diagnostic Oligonucleotide Probe Sets for DNA Microarrays. IPDPS Andreas Krause, Markus Kräutner, Harald Meier
2003	—	`conf`	Mobile wireless acess to EHR and PACS in clinical practice. MoCoMed K. Heiss, Andreas Krause, Alexander T. Mehlhorn, V. Riedl, S. Preis, K. Feike, L. Greiner, Dominik Hartl
2003	—	`conf`	PDA-based decision support and documentation for transplantation surgery data. MoCoMed Andreas Krause, Alexander T. Mehlhorn, Dominik Hartl, V. Riedl, S. Preis, K. Feike, L. Greiner, Klaus-E. Gerauer, Manfred Stangl
2003	Misc	`conf`	SenSay: A Context-Aware Mobile Phone. ISWC Daniel P. Siewiorek, Asim Smailagic, Junichi Furukawa, Andreas Krause, Neema Moraveji, Kathryn Reiger, Jeremy Shaffer, Fei Lung Wong
2003	Misc	`conf`	Unsupervised, Dynamic Identification of Physiological and Activity Context in Wearable Computing. ISWC Andreas Krause, Daniel P. Siewiorek, Asim Smailagic, Jonny Farringdon