UAI A

202 papers

YearTitle / Authors
2024A General Identification Algorithm For Data Fusion Problems Under Systematic Selection.
Jaron Jia Rong Lee, AmirEmad Ghassami, Ilya Shpitser
2024A Generalized Bayesian Approach to Distribution-on-Distribution Regression.
Tin Lok James Ng
2024A Global Markov Property for Solutions of Stochastic Difference Equations and the corresponding Full Time Graphs.
Tom Hochsprung, Jakob Runge, Andreas Gerhardus
2024A Graph Theoretic Approach for Preference Learning with Feature Information.
Aadirupa Saha, Arun Rajkumar
2024A Homogenization Approach for Gradient-Dominated Stochastic Optimization.
Jiyuan Tan, Chenyu Xue, Chuwen Zhang, Qi Deng, Dongdong Ge, Yinyu Ye
2024Active Learning Framework for Incomplete Networks.
Tung Khong, Cong Tran, Cuong Pham
2024Adaptive Softmax Trees for Many-Class Classification.
Rasul Kairgeldin, Magzhan Gabidolla, Miguel Á. Carreira-Perpiñán
2024Adaptive Time-Stepping Schedules for Diffusion Models.
Yuzhu Chen, Fengxiang He, Shi Fu, Xinmei Tian, Dacheng Tao
2024Adjustment Identification Distance: A gadjid for Causal Structure Learning.
Leonard Henckel, Theo Würtzen, Sebastian Weichwald
2024Amortized Variational Inference: When and Why?
Charles C. Margossian, David M. Blei
2024Analysis of Bootstrap and Subsampling in High-dimensional Regularized Regression.
Lucas Clarté, Adrien Vandenbroucque, Guillaume Dalle, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
2024Anomaly Detection with Variance Stabilized Density Estimation.
Amit Rozner, Barak Battash, Henry Li, Lior Wolf, Ofir Lindenbaum
2024Approximate Bayesian Computation with Path Signatures.
Joel Dyer, Patrick Cannon, Sebastian M. Schmon
2024Approximate Kernel Density Estimation under Metric-based Local Differential Privacy.
Yi Zhou, Yanhao Wang, Long Teng, Qiang Huang, Cen Chen
2024Approximation Algorithms for Observer Aware MDPs.
Shuwa Miura, Olivier Buffet, Shlomo Zilberstein
2024AutoDrop: Training Deep Learning Models with Automatic Learning Rate Drop.
Jing Wang, Yunfei Teng, Anna Choromanska
2024BEARS Make Neuro-Symbolic Models Aware of their Reasoning Shortcuts.
Emanuele Marconato, Samuele Bortolotti, Emile van Krieken, Antonio Vergari, Andrea Passerini, Stefano Teso
2024BanditQ: Fair Bandits with Guaranteed Rewards.
Abhishek Sinha
2024Bandits with Knapsacks and Predictions.
Davide Drago, Andrea Celli, Marek Eliás
2024Base Models for Parabolic Partial Differential Equations.
Xingzi Xu, Ali Hasan, Jie Ding, Vahid Tarokh
2024Bayesian Active Learning in the Presence of Nuisance Parameters.
Sabina J. Sloman, Ayush Bharti, Julien Martinelli, Samuel Kaski
2024Bayesian Pseudo-Coresets via Contrastive Divergence.
Piyush Tiwary, Kumar Shubham, Vivek Kashyap, Prathosh A. P.
2024Beyond Dirichlet-based Models: When Bayesian Neural Networks Meet Evidential Deep Learning.
Hanjing Wang, Qiang Ji
2024Bias-aware Boolean Matrix Factorization Using Disentangled Representation Learning.
Xiao Wang, Jia Wang, Tong Zhao, Yijie Wang, Nan Zhang, Yong Zang, Sha Cao, Chi Zhang
2024Bootstrap Your Conversions: Thompson Sampling for Partially Observable Delayed Rewards.
Marco Gigli, Fabio Stella
2024Bounding causal effects with leaky instruments.
David S. Watson, Jordan Penn, Lee M. Gunderson, Gecia Bravo Hermsdorff, Afsaneh Mastouri, Ricardo Silva
2024CSS: Contrastive Semantic Similarities for Uncertainty Quantification of LLMs.
Shuang Ao, Stefan Rueger, Advaith Siddharthan
2024Calibrated and Conformal Propensity Scores for Causal Effect Estimation.
Shachi Deshpande, Volodymyr Kuleshov
2024Can we Defend Against the Unknown? An Empirical Study About Threshold Selection for Neural Network Monitoring.
Khoi Tran Dang, Kevin Delmas, Jérémie Guiochet, Joris Guérin
2024Causal Discovery with Deductive Reasoning: One Less Problem.
Jonghwan Kim, Inwoo Hwang, Sanghack Lee
2024Causally Abstracted Multi-armed Bandits.
Fabio Massimo Zennaro, Nicholas Bishop, Joel Dyer, Yorgos Felekis, Anisoara Calinescu, Michael J. Wooldridge, Theodoros Damoulas
2024Center-Based Relaxed Learning Against Membership Inference Attacks.
Xingli Fang, Jung-Eun Kim
2024Characterising Interventions in Causal Games.
Manuj Mishra, James Fox, Michael J. Wooldridge
2024Characterizing Data Point Vulnerability as Average-Case Robustness.
Tessa Han, Suraj Srinivas, Himabindu Lakkaraju
2024Cold-start Recommendation by Personalized Embedding Region Elicitation.
Hieu Trung Nguyen, Duy Nguyen, Khoa D. Doan, Viet Anh Nguyen
2024Common Event Tethering to Improve Prediction of Rare Clinical Events.
Quinn Lanners, Qin Weng, Marie-Louise Meng, Matthew M. Engelhard
2024Computing Low-Entropy Couplings for Large-Support Distributions.
Samuel Sokota, Dylan Sam, Christian Schröder de Witt, Spencer Compton, Jakob N. Foerster, J. Zico Kolter
2024Conditional Bayesian Quadrature.
Zonghao Chen, Masha Naslidnyk, Arthur Gretton, François-Xavier Briol
2024Consistency Regularization for Domain Generalization with Logit Attribution Matching.
Han Gao, Kaican Li, Weiyan Xie, Zhi Lin, Yongxiang Huang, Luning Wang, Caleb Chen Cao, Nevin L. Zhang
2024ContextFlow++: Generalist-Specialist Flow-based Generative Models with Mixed-variable Context Encoding.
Denis A. Gudovskiy, Tomoyuki Okuno, Yohei Nakata
2024Convergence Behavior of an Adversarial Weak Supervision Method.
Steven An, Sanjoy Dasgupta
2024Cooperative Meta-Learning with Gradient Augmentation.
Jongyun Shin, Seungjin Han, Jangho Kim
2024Cost-Sensitive Uncertainty-Based Failure Recognition for Object Detection.
Moussa Kassem Sbeyti, Michelle Karg, Christian Wirth, Nadja Klein, Sahin Albayrak
2024DataSP: A Differential All-to-All Shortest Path Algorithm for Learning Costs and Predicting Paths with Context.
Alan A. Lahoud, Erik Schaffernicht, Johannes A. Stork
2024Decentralized Online Learning in General-Sum Stackelberg Games.
Yaolong Yu, Haipeng Chen
2024Decentralized Two-Sided Bandit Learning in Matching Market.
Yirui Zhang, Zhixuan Fang
2024Decision-Focused Evaluation of Worst-Case Distribution Shift.
Kevin Ren, Yewon Byun, Bryan Wilder
2024Detecting critical treatment effect bias in small subgroups.
Piersilvio De Bartolomeis, Javier Abad, Konstantin Donhauser, Fanny Yang
2024Differentiable Pareto-Smoothed Weighting for High-Dimensional Heterogeneous Treatment Effect Estimation.
Yoichi Chikahara, Kansei Ushiyama
2024Differentially Private No-regret Exploration in Adversarial Markov Decision Processes.
Shaojie Bai, Lanting Zeng, Chengcheng Zhao, Xiaoming Duan, Mohammad Sadegh Talebi, Peng Cheng, Jiming Chen
2024Dirichlet Continual Learning: Tackling Catastrophic Forgetting in NLP.
Min Zeng, Haiqin Yang, Wei Xue, Qifeng Liu, Yike Guo
2024Discrete Probabilistic Inference as Control in Multi-path Environments.
Tristan Deleu, Padideh Nouri, Nikolay Malkin, Doina Precup, Yoshua Bengio
2024DistriBlock: Identifying adversarial audio samples by leveraging characteristics of the output distribution.
Matías P. Pizarro B., Dorothea Kolossa, Asja Fischer
2024Distributionally Robust Optimization as a Scalable Framework to Characterize Extreme Value Distributions.
Patrick K. Kuiper, Ali Hasan, Wenhao Yang, Yuting Ng, Hoda Bidkhori, Jose H. Blanchet, Vahid Tarokh
2024Domain Adaptation with Cauchy-Schwarz Divergence.
Wenzhe Yin, Shujian Yu, Yicong Lin, Jie Liu, Jan-Jakob Sonke, Efstratios Gavves
2024Early-Exit Neural Networks with Nested Prediction Sets.
Metod Jazbec, Patrick Forré, Stephan Mandt, Dan Zhang, Eric T. Nalisnick
2024Efficient Interactive Maximization of BP and Weakly Submodular Objectives.
Adhyyan Narang, Omid Sadeghi, Lillian J. Ratliff, Maryam Fazel, Jeff A. Bilmes
2024Efficient Monte Carlo Tree Search via On-the-Fly State-Conditioned Action Abstraction.
Yunhyeok Kwak, Inwoo Hwang, Dooyoung Kim, Sanghack Lee, Byoung-Tak Zhang
2024Efficiently Deciding Algebraic Equivalence of Bow-Free Acyclic Path Diagrams.
Thijs van Ommen
2024End-to-End Learning for Fair Multiobjective Optimization Under Uncertainty.
My H. Dinh, James Kotary, Ferdinando Fioretto
2024End-to-end Conditional Robust Optimization.
Abhilash Reddy Chenreddy, Erick Delage
2024Enhancing Patient Recruitment Response in Clinical Trials: an Adaptive Learning Framework.
Xinying Fang, Shouhao Zhou
2024EntProp: High Entropy Propagation for Improving Accuracy and Robustness.
Shohei Enomoto
2024Equilibrium Computation in Multidimensional Congestion Games: CSP and Learning Dynamics Approaches.
Mohammad T. Irfan, Hau Chan, Jared Soundy
2024Evaluating Bayesian deep learning for radio galaxy classification.
Devina Mohan, Anna M. M. Scaife
2024Exploring High-dimensional Search Space via Voronoi Graph Traversing.
Aidong Zhao, Xuyang Zhao, Tianchen Gu, Zhaori Bi, Xinwei Sun, Changhao Yan, Fan Yang, Dian Zhou, Xuan Zeng
2024Extremely Greedy Equivalence Search.
Achille Nazaret, David M. Blei
2024Fair Active Learning in Low-Data Regimes.
Romain Camilleri, Andrew Wagenmaker, Jamie Morgenstern, Lalit Jain, Kevin Jamieson
2024Fast Interactive Search under a Scale-Free Comparison Oracle.
Daniyar Chumbalov, Lars Klein, Lucas Maystre, Matthias Grossglauser
2024Fast Reliability Estimation for Neural Networks with Adversarial Attack-Driven Importance Sampling.
Karim Tit, Teddy Furon
2024Faster Perfect Sampling of Bayesian Network Structures.
Juha Harviainen, Mikko Koivisto
2024FedAST: Federated Asynchronous Simultaneous Training.
Baris Askin, Pranay Sharma, Carlee Joe-Wong, Gauri Joshi
2024Finite-Time Analysis of Three-Timescale Constrained Actor-Critic and Constrained Natural Actor-Critic Algorithms.
Prashansa Panda, Shalabh Bhatnagar
2024Functional Wasserstein Bridge Inference for Bayesian Deep Learning.
Mengjing Wu, Junyu Xuan, Jie Lu
2024Functional Wasserstein Variational Policy Optimization.
Junyu Xuan, Mengjing Wu, Zihe Liu, Jie Lu
2024GCVR: Reconstruction from Cross-View Enable Sufficient and Robust Graph Contrastive Learning.
Qianlong Wen, Zhongyu Ouyang, Chunhui Zhang, Yiyue Qian, Chuxu Zhang, Yanfang Ye
2024GeONet: a neural operator for learning the Wasserstein geodesic.
Andrew Gracyk, Xiaohui Chen
2024General Markov Model for Solving Patrolling Games.
Andrzej Nagórko, Marcin Waniek, Malgorzata Róg, Michal Tomasz Godziszewski, Barbara Rosiak, Tomasz Pawel Michalak
2024Generalization and Learnability in Multiple Instance Regression.
Kushal Chauhan, Rishi Saket, Lorne Applebaum, Ashwinkumar Badanidiyuru, Chandan Giri, Aravindan Raghuveer
2024Generalized Expected Utility as a Universal Decision Rule - A Step Forward.
Hélène Fargier, Pierre Pomeret-Coquot
2024Gradient descent in matrix factorization: Understanding large initialization.
Hengchao Chen, Xin Chen, Mohamad Elmasri, Qiang Sun
2024Graph Contrastive Learning under Heterophily via Graph Filters.
Wenhan Yang, Baharan Mirzasoleiman
2024Graph Feedback Bandits with Similar Arms.
Han Qi, Guo Fei, Li Zhu
2024Group Fairness in Predict-Then-Optimize Settings for Restless Bandits.
Shresth Verma, Yunfan Zhao, Sanket Shah, Niclas Boehmer, Aparna Taneja, Milind Tambe
2024Guaranteeing Robustness Against Real-World Perturbations In Time Series Classification Using Conformalized Randomized Smoothing.
Nicola Franco, Jakob Spiegelberg, Jeanette Miriam Lorenz, Stephan Günnemann
2024Hidden Population Estimation with Indirect Inference and Auxiliary Information.
Justin Weltz, Eric Laber, Alexander Volfovsky
2024How Inverse Conditional Flows Can Serve as a Substitute for Distributional Regression.
Lucas Kook, Chris Kolb, Philipp Schiele, Daniel Dold, Marcel Arpogaus, Cornelius Fritz, Philipp F. M. Baumann, Philipp Kopper, Tobias Pielok, Emilio Dorigatti, David Rügamer
2024How to Fix a Broken Confidence Estimator: Evaluating Post-hoc Methods for Selective Classification with Deep Neural Networks.
Luís Felipe P. Cattelan, Danilo Silva
2024Hybrid CtrlFormer: Learning Adaptive Search Space Partition for Hybrid Action Control via Transformer-based Monte Carlo Tree Search.
Jiashun Liu, Xiaotian Hao, Jianye Hao, Yan Zheng, Yujing Hu, Changjie Fan, Tangjie Lv, Zhipeng Hu
2024ILP-FORMER: Solving Integer Linear Programming with Sequence to Multi-Label Learning.
Shufeng Kong, Caihua Liu, Carla Gomes
2024Identifiability of total effects from abstractions of time series causal graphs.
Charles K. Assaad, Emilie Devijver, Éric Gaussier, Gregor Goessler, Anouar Meynaoui
2024Identification and Estimation of Conditional Average Partial Causal Effects via Instrumental Variable.
Yuta Kawakami, Manabu Kuroki, Jin Tian
2024Identifying Causal Changes Between Linear Structural Equation Models.
Vineet Malik, Kevin Bello, Asish Ghoshal, Jean Honorio
2024Identifying Homogeneous and Interpretable Groups for Conformal Prediction.
Natalia Martinez Gil, Dhaval Patel, Chandra Reddy, Giridhar Ganapavarapu, Roman Vaculín, Jayant Kalagnanam
2024Inference for Optimal Linear Treatment Regimes in Personalized Decision-making.
Yuwen Cheng, Shu Yang
2024Inference in Probabilistic Answer Set Programs with Imprecise Probabilities via Optimization.
Damiano Azzolini, Fabrizio Riguzzi
2024Invariant Causal Prediction with Local Models.
Alexander Mey, Rui Manuel Castro
2024Investigating the Impact of Model Width and Density on Generalization in Presence of Label Noise.
Yihao Xue, Kyle Whitecross, Baharan Mirzasoleiman
2024Iterated INLA for State and Parameter Estimation in Nonlinear Dynamical Systems.
Rafael Anderka, Marc Peter Deisenroth, So Takao
2024Knowledge Intensive Learning of Credal Networks.
Saurabh Mathur, Alessandro Antonucci, Sriraam Natarajan
2024Label Consistency-based Worker Filtering for Crowdsourcing.
Jiao Li, Liangxiao Jiang, Chaoqun Li, Wenjun Zhang
2024Label-wise Aleatoric and Epistemic Uncertainty Quantification.
Yusuf Sale, Paul Hofman, Timo Löhr, Lisa Wimmer, Thomas Nagler, Eyke Hüllermeier
2024Last-iterate Convergence Separation between Extra-gradient and Optimism in Constrained Periodic Games.
Yi Feng, Ping Li, Ioannis Panageas, Xiao Wang
2024Latent Representation Entropy Density for Distribution Shift Detection.
Fabio Arnez, Daniel Alfonso Montoya Vasquez, Ansgar Radermacher, François Terrier
2024Learning Accurate and Interpretable Decision Trees.
Maria-Florina Balcan, Dravyansh Sharma
2024Learning Causal Abstractions of Linear Structural Causal Models.
Riccardo Massidda, Sara Magliacane, Davide Bacciu
2024Learning Distributionally Robust Tractable Probabilistic Models in Continuous Domains.
Hailiang Dong, James Amato, Vibhav Gogate, Nicholas Ruozzi
2024Learning Topological Representations with Bidirectional Graph Attention Network for Solving Job Shop Scheduling Problem.
Cong Zhang, Zhiguang Cao, Yaoxin Wu, Wen Song, Jing Sun
2024Learning from Crowds with Dual-View K-Nearest Neighbor.
Jiao Li, Liangxiao Jiang, Xue Wu, Wenjun Zhang
2024Learning relevant contextual variables within Bayesian optimization.
Julien Martinelli, Ayush Bharti, Armi Tiihonen, S. T. John, Louis Filstroff, Sabina J. Sloman, Patrick Rinke, Samuel Kaski
2024Learning to Rank for Active Learning via Multi-Task Bilevel Optimization.
Zixin Ding, Si Chen, Ruoxi Jia, Yuxin Chen
2024Linear Opinion Pooling for Uncertainty Quantification on Graphs.
Clemens Damke, Eyke Hüllermeier
2024Linearly Constrained Gaussian Processes are SkewGPs: application to Monotonic Preference Learning and Desirability.
Alessio Benavoli, Dario Azzimonti
2024Local Discovery by Partitioning: Polynomial-Time Causal Discovery Around Exposure-Outcome Pairs.
Jacqueline R. M. A. Maasch, Weishen Pan, Shantanu Gupta, Volodymyr Kuleshov, Kyra Gan, Fei Wang
2024Localised Natural Causal Learning Algorithms for Weak Consistency Conditions.
Kai Z. Teh, Kayvan Sadeghi, Terry Soo
2024Low-rank Matrix Bandits with Heavy-tailed Rewards.
Yue Kang, Cho-Jui Hsieh, Thomas Chun Man Lee
2024Masking the Unknown: Leveraging Masked Samples for Enhanced Data Augmentation.
Xun Yao, Zijian Huang, Xinrong Hu, Jie Yang, Yi Guo
2024Memorization Capacity for Additive Fine-Tuning with Small ReLU Networks.
Jy-yong Sohn, Dohyun Kwon, Seoyeon An, Kangwook Lee
2024MetaCOG: A Heirarchical Probabilistic Model for Learning Meta-Cognitive Visual Representations.
Marlene Berke, Zhangir Azerbayev, Mario Belledonne, Zenna Tavares, Julian Jara-Ettinger
2024Metric Learning from Limited Pairwise Preference Comparisons.
Zhi Wang, Geelon So, Ramya Korlakai Vinayak
2024Mitigating Overconfidence in Out-of-Distribution Detection by Capturing Extreme Activations.
Mohammad Azizmalayeri, Ameen Abu-Hanna, Giovanni Cinà
2024Model-Free Robust Reinforcement Learning with Sample Complexity Analysis.
Yudan Wang, Shaofeng Zou, Yue Wang
2024Multi-Relational Structural Entropy.
Yuwei Cao, Hao Peng, Angsheng Li, Chenyu You, Zhifeng Hao, Philip S. Yu
2024Multi-fidelity Bayesian Optimization with Multiple Information Sources of Input-dependent Fidelity.
Mingzhou Fan, Byung-Jun Yoon, Edward R. Dougherty, Nathan M. Urban, Francis J. Alexander, Raymundo Arróyave, Xiaoning Qian
2024Multi-layer random features and the approximation power of neural networks.
Rustem Takhanov
2024Neighbor Similarity and Multimodal Alignment based Product Recommendation Study.
Zhiqiang Zhang, Yongqiang Jiang, Qian Gao, Zhipeng Wang
2024Neural Active Learning Meets the Partial Monitoring Framework.
Maxime Heuillet, Ola Ahmad, Audrey Durand
2024Neural Architecture Search Finds Robust Models by Knowledge Distillation.
Utkarsh Nath, Yancheng Wang, Yingzhen Yang
2024Neural Optimal Transport with Lagrangian Costs.
Aram-Alexandre Pooladian, Carles Domingo-Enrich, Ricky T. Q. Chen, Brandon Amos
2024No-Regret Learning of Nash Equilibrium for Black-Box Games via Gaussian Processes.
Minbiao Han, Fengxue Zhang, Yuxin Chen
2024Non-stationary Domain Generalization: Theory and Algorithm.
Thai-Hoang Pham, Xueru Zhang, Ping Zhang
2024Normalizing Flows for Conformal Regression.
Nicolò Colombo
2024Offline Bayesian Aleatoric and Epistemic Uncertainty Quantification and Posterior Value Optimisation in Finite-State MDPs.
Filippo Valdettaro, Aldo Faisal
2024Offline Reward Perturbation Boosts Distributional Shift in Online RL.
Zishun Yu, Siteng Kang, Xinhua Zhang
2024On Convergence of Federated Averaging Langevin Dynamics.
Wei Deng, Qian Zhang, Yian Ma, Zhao Song, Guang Lin
2024On Hardware-efficient Inference in Probabilistic Circuits.
Lingyun Yao, Martin Trapp, Jelin Leslin, Gaurav Singh, Peng Zhang, Karthekeyan Periasamy, Martin Andraud
2024On Overcoming Miscalibrated Conversational Priors in LLM-based ChatBots.
Christine Herlihy, Jennifer Neville, Tobias Schnabel, Adith Swaminathan
2024On the Capacitated Facility Location Problem with Scarce Resources.
Gennaro Auricchio, Harry J. Clough, Jie Zhang
2024On the Convergence of Hierarchical Federated Learning with Partial Worker Participation.
Xiaohan Jiang, Hongbin Zhu
2024On the Inductive Biases of Demographic Parity-based Fair Learning Algorithms.
Haoyu Lei, Amin Gohari, Farzan Farnia
2024One Shot Inverse Reinforcement Learning for Stochastic Linear Bandits.
Etash Guha, Jim James, Krishna Acharya, Vidya Muthukumar, Ashwin Pananjady
2024Online Policy Optimization for Robust Markov Decision Process.
Jing Dong, Jingwei Li, Baoxiang Wang, Jingzhao Zhang
2024Optimistic Regret Bounds for Online Learning in Adversarial Markov Decision Processes.
Sang Bin Moon, Abolfazl Hashemi
2024Optimization Framework for Semi-supervised Attributed Graph Coarsening.
Manoj Kumar, Subhanu Halder, Archit Kane, Ruchir Gupta, Sandeep Kumar
2024Optimizing Language Models for Human Preferences is a Causal Inference Problem.
Victoria Lin, Eli Ben-Michael, Louis-Philippe Morency
2024Partial Identification with Proxy of Latent Confoundings via Sum-of-ratios Fractional Programming.
Zhiheng Zhang, Xinyan Su
2024Partial identification of the maximum mean discrepancy with mismeasured data.
Ron Nafshi, Maggie Makar
2024Patch-Prompt Aligned Bayesian Prompt Tuning for Vision-Language Models.
Xinyang Liu, Dongsheng Wang, Bowei Fang, Miaoge Li, Yishi Xu, Zhibin Duan, Bo Chen, Mingyuan Zhou
2024Performative Reinforcement Learning in Gradually Shifting Environments.
Ben Rank, Stelios Triantafyllou, Debmalya Mandal, Goran Radanovic
2024Pix2Code: Learning to Compose Neural Visual Concepts as Programs.
Antonia Wüst, Wolfgang Stammer, Quentin Delfosse, Devendra Singh Dhami, Kristian Kersting
2024Polynomial Semantics of Tractable Probabilistic Circuits.
Oliver Broadrick, Honghua Zhang, Guy Van den Broeck
2024Posterior Inference on Shallow Infinitely Wide Bayesian Neural Networks under Weights with Unbounded Variance.
Jorge Loría, Anindya Bhadra
2024Power Mean Estimation in Stochastic Monte-Carlo Tree Search.
Tuan Dam, Odalric-Ambrym Maillard, Emilie Kaufmann
2024Preface.
2024Privacy-Aware Randomized Quantization via Linear Programming.
Zhongteng Cai, Xueru Zhang, Mohammad Mahdi Khalili
2024Probabilistic reconciliation of mixed-type hierarchical time series.
Lorenzo Zambon, Dario Azzimonti, Nicolò Rubattu, Giorgio Corani
2024Probabilities of Causation for Continuous and Vector Variables.
Yuta Kawakami, Manabu Kuroki, Jin Tian
2024Products, Abstractions and Inclusions of Causal Spaces.
Simon Buchholz, Junhyung Park, Bernhard Schölkopf
2024Publishing Number of Walks and Katz Centrality under Local Differential Privacy.
Louis Betzer, Vorapong Suppakitpaisarn, Quentin Hillebrand
2024Pure Exploration in Asynchronous Federated Bandits.
Zichen Wang, Chuanhao Li, Chenyu Song, Lianghui Wang, Quanquan Gu, Huazheng Wang
2024QuantProb: Generalizing Probabilities along with Predictions for a Pre-trained Classifier.
Aditya Challa, Soma S. Dhavala, Snehanshu Saha
2024Quantifying Local Model Validity using Active Learning.
Sven Lämmle, Can Bogoclu, Robert Vosshall, Anselm Haselhoff, Dirk Roos
2024Quantifying Representation Reliability in Self-Supervised Learning Models.
Young-Jin Park, Hao Wang, Shervin Ardeshir, Navid Azizan
2024Quantization of Large Language Models with an Overdetermined Basis.
Daniil Merkulov, Daria Cherniuk, Alexander Rudikov, Ivan V. Oseledets, Ekaterina A. Muravleva, Aleksandr Mikhalev, Boris Kashin
2024Quantum Kernelized Bandits.
Yasunari Hikima, Kazunori Murao, Sho Takemori, Yuhei Umeda
2024RE-SORT: Removing Spurious Correlation in Multilevel Interaction for CTR Prediction.
SongLi Wu, Liang Du, Jiaqi Yang, Yuai Wang, De-Chuan Zhan, Shuang Zhao, Zixun Sun
2024Random Linear Projections Loss for Hyperplane-Based Optimization in Neural Networks.
Shyam Venkatasubramanian, Ahmed Aloui, Vahid Tarokh
2024Recursively-Constrained Partially Observable Markov Decision Processes.
Qi Heng Ho, Tyler J. Becker, Benjamin Kraske, Zakariya Laouar, Martin S. Feather, Federico Rossi, Morteza Lahijanian, Zachary Sunberg
2024Reflected Schrödinger Bridge for Constrained Generative Modeling.
Wei Deng, Yu Chen, Nicole Tianjiao Yang, Hengrong Du, Qi Feng, Ricky Tian Qi Chen
2024Response Time Improves Gaussian Process Models for Perception and Preferences.
Michael Shvartsman, Benjamin Letham, Eytan Bakshy, Stephen Keeley
2024Revisiting Convergence of AdaGrad with Relaxed Assumptions.
Yusu Hong, Junhong Lin
2024Revisiting Kernel Attention with Correlated Gaussian Process Representation.
Long Minh Bui, Tho Tran Huu, Duy Dinh, Tan Minh Nguyen, Trong Nghia Hoang
2024Robust Entropy Search for Safe Efficient Bayesian Optimization.
Dorina Weichert, Alexander Kister, Sebastian Houben, Patrick Link, Gunar Ernis
2024SMuCo: Reinforcement Learning for Visual Control via Sequential Multi-view Total Correlation.
Tong Cheng, Hang Dong, Lu Wang, Bo Qiao, Qingwei Lin, Saravan Rajmohan, Thomas Moscibroda
2024Sample Average Approximation for Black-Box Variational Inference.
Javier Burroni, Justin Domke, Daniel Sheldon
2024Shedding Light on Large Generative Networks: Estimating Epistemic Uncertainty in Diffusion Models.
Lucas Berry, Axel Brando, David Meger
2024Sound Heuristic Search Value Iteration for Undiscounted POMDPs with Reachability Objectives.
Qi Heng Ho, Martin S. Feather, Federico Rossi, Zachary Sunberg, Morteza Lahijanian
2024Statistical and Causal Robustness for Causal Null Hypothesis Tests.
Junhui Yang, Rohit Bhattacharya, Youjin Lee, Ted Westling
2024Stein Random Feature Regression.
Houston Warren, Rafael Oliveira, Fabio T. Ramos
2024Support Recovery in Sparse PCA with General Missing Data.
Hanbyul Lee, Qifan Song, Jean Honorio
2024Targeted Reduction of Causal Models.
Armin Kekic, Bernhard Schölkopf, Michel Besserve
2024The Real Deal Behind the Artificial Appeal: Inferential Utility of Tabular Synthetic Data.
Alexander Decruyenaere, Heidelinde Dehaene, Paloma Rabaey, Christiaan Polet, Johan Decruyenaere, Stijn Vansteelandt, Thomas Demeester
2024To smooth a cloud or to pin it down: Expressiveness guarantees and insights on score matching in denoising diffusion models.
Teodora Reu, Francisco Vargas, Anna Kerekes, Michael M. Bronstein
2024Towards Bounding Causal Effects under Markov Equivalence.
Alexis Bellot
2024Towards Minimax Optimality of Model-based Robust Reinforcement Learning.
Pierre Clavier, Erwan Le Pennec, Matthieu Geist
2024Towards Representation Learning for Weighting Problems in Design-Based Causal Inference.
Oscar Clivio, Avi Feller, Chris C. Holmes
2024Towards Scalable Bayesian Transformers: Investigating stochastic subset selection for NLP.
Peter Johannes Tejlgaard Kampen, Gustav Ragnar Stoettrup Als, Michael Riis Andersen
2024Transductive and Inductive Outlier Detection with Robust Autoencoders.
Ofir Lindenbaum, Yariv Aizenbud, Yuval Kluger
2024Trusted re-weighting for label distribution learning.
Zhuoran Zheng, Chen Wu, Yeying Jin, Xiuyi Jia
2024Two Facets of SDE Under an Information-Theoretic Lens: Generalization of SGD via Training Trajectories and via Terminal States.
Ziqiao Wang, Yongyi Mao
2024Uncertainty Estimation with Recursive Feature Machines.
Daniel Gedon, Amirhesam Abedsoltan, Thomas B. Schön, Mikhail Belkin
2024Uncertainty in Artificial Intelligence, 15-19 July 2024, Universitat Pompeu Fabra, Barcelona, Spain.
Negar Kiyavash, Joris M. Mooij
2024Understanding Pathologies of Deep Heteroskedastic Regression.
Eliot Wong-Toi, Alex Boyd, Vincent Fortuin, Stephan Mandt
2024Unified PAC-Bayesian Study of Pessimism for Offline Policy Learning with Regularized Importance Sampling.
Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba
2024Unsupervised Feature Selection towards Pattern Discrimination Power.
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