Kevin Jamieson

146 papers A* 38A 14B 1Misc 2Journal 82Unranked 9
YearRankTypeTitle / Venue / Authors
2026 J jnl
Efficient Uncoupled Learning Dynamics with ~O}(T
CoRR
Arnab Maiti, Claire Jie Zhang, Kevin Jamieson, Jamie H. Morgenstern, Ioannis Panageas, Lillian J. Ratliff
2026 J jnl
Minimax Optimal Strategy for Delayed Observations in Online Reinforcement Learning.
CoRR
Harin Lee, Kevin Jamieson
2026 J jnl
On The Complexity of Best-Arm Identification in Non-Stationary Linear Bandits.
CoRR
Leo Maynard-Zhang, Zhihan Xiong, Kevin Jamieson, Maryam Fazel
2026 J jnl
Revisiting the Bertrand Paradox via Equilibrium Analysis of No-regret Learners.
CoRR
Arnab Maiti, Junyan Liu, Kevin Jamieson, Lillian J. Ratliff
2025 J jnl
Adapting to Stochastic and Adversarial Losses in Episodic MDPs with Aggregate Bandit Feedback.
CoRR
Shinji Ito, Kevin Jamieson, Haipeng Luo, Arnab Maiti, Taira Tsuchiya
2025 A* conf
Efficient Near-Optimal Algorithm for Online Shortest Paths in Directed Acyclic Graphs with Bandit Feedback Against Adaptive Adversaries.
COLT
Arnab Maiti, Zhiyuan Fan, Kevin Jamieson, Lillian J. Ratliff, Gabriele Farina
2025 J jnl
Efficient Near-Optimal Algorithm for Online Shortest Paths in Directed Acyclic Graphs with Bandit Feedback Against Adaptive Adversaries.
CoRR
Arnab Maiti, Zhiyuan Fan, Kevin Jamieson, Lillian J. Ratliff, Gabriele Farina
2025 J jnl
High Effort, Low Gain: Fundamental Limits of Active Learning for Linear Dynamical Systems.
CoRR
Nicolas Chatzikiriakos, Kevin Jamieson, Andrea Iannelli
2025 J jnl
Improved Regret Bounds for Linear Bandits with Heavy-Tailed Rewards.
CoRR
Artin Tajdini, Jonathan Scarlett, Kevin Jamieson
2025 A* conf
Learning to Incentivize in Repeated Principal-Agent Problems with Adversarial Agent Arrivals.
ICML
Junyan Liu, Arnab Maiti, Artin Tajdini, Kevin Jamieson, Lillian J. Ratliff
2025 J jnl
Learning to Incentivize in Repeated Principal-Agent Problems with Adversarial Agent Arrivals.
CoRR
Junyan Liu, Arnab Maiti, Artin Tajdini, Kevin Jamieson, Lillian J. Ratliff
2025 B conf
On the Limitations and Possibilities of Nash Regret Minimization in Zero-Sum Matrix Games Under Noisy Feedback.
SAGT
Arnab Maiti, Kevin Jamieson, Lillian J. Ratliff
2025 J jnl
On the Universal Near Optimality of Hedge in Combinatorial Settings.
CoRR
Zhiyuan Fan, Arnab Maiti, Kevin Jamieson, Lillian J. Ratliff, Gabriele Farina
2025 J jnl
Query-Efficient Algorithm to Find all Nash Equilibria in a Two-Player Zero-Sum Matrix Game.
ACM Trans. Economics and Comput.
Arnab Maiti, Ross Boczar, Kevin Jamieson, Lillian J. Ratliff
2025 J jnl
Stow: Robotic Packing of Items into Fabric Pods.
CoRR
Nicolas Hudson, Josh Hooks, Rahul Warrier, Curt Salisbury, Ross Hartley, Kislay Kumar, Bhavana Chandrashekhar, Paul Birkmeyer, Bosch Tang, Matthew A. Frost, Shantanu Thakar, Tony Piaskowy, Petter Nilsson, Josh Petersen, Neel Doshi, Alan Slatter, Ankit Bhatia, Cassie Meeker, Yuechuan Xue, Dylan Cox, Alex Kyriazis, Bai Lou, Nadeem Hasan, Asif Rana, Nikhil Chacko, Ruinian Xu, Siamak Faal, Esi Seraj, Mudit Agrawal, Kevin Jamieson, Alessio Bisagni, Valerie Samzun, Christine Fuller, Alex Keklak, Alex Frenkel, Lillian J. Ratliff, Aaron Parness
2025 J jnl
Unbiased Identification of Broadly Appealing Content Using a Pure Exploration Infinitely Armed Bandit Strategy.
Trans. Recomm. Syst.
Maryam Aziz, Jesse Anderton, Kevin Jamieson, Alice Wang, Hugues Bouchard, Javed A. Aslam
2024 A conf
A/B Testing and Best-arm Identification for Linear Bandits with Robustness to Non-stationarity.
AISTATS
Zhihan Xiong, Romain Camilleri, Maryam Fazel, Lalit Jain, Kevin Jamieson
2024 A* conf
Active learning of neural population dynamics using two-photon holographic optogenetics.
NeurIPS
Andrew Wagenmaker, Lu Mi, Marton Rozsa, Matthew S. Bull, Karel Svoboda, Kayvon Daie, Matthew D. Golub, Kevin Jamieson
2024 J jnl
Active learning of neural population dynamics using two-photon holographic optogenetics.
CoRR
Andrew Wagenmaker, Lu Mi, Marton Rozsa, Matthew S. Bull, Karel Svoboda, Kayvon Daie, Matthew D. Golub, Kevin Jamieson
2024 — conf
An Experimental Design Framework for Label-Efficient Supervised Finetuning of Large Language Models.
ACL (Findings)
Gantavya Bhatt, Yifang Chen, Arnav Mohanty Das, Jifan Zhang, Sang T. Truong, Stephen Mussmann, Yinglun Zhu, Jeff A. Bilmes, Simon S. Du, Kevin Jamieson, Jordan T. Ash, Robert D. Nowak
2024 J jnl
An Experimental Design Framework for Label-Efficient Supervised Finetuning of Large Language Models.
CoRR
Gantavya Bhatt, Yifang Chen, Arnav Mohanty Das, Jifan Zhang, Sang T. Truong, Stephen Mussmann, Yinglun Zhu, Jeffrey A. Bilmes, Simon S. Du, Kevin Jamieson, Jordan T. Ash, Robert D. Nowak
2024 A* conf
CLIPLoss and Norm-Based Data Selection Methods for Multimodal Contrastive Learning.
NeurIPS
Yiping Wang, Yifang Chen, Wendan Yan, Alex Fang, Wenjing Zhou, Kevin Jamieson, Simon S. Du
2024 J jnl
CLIPLoss and Norm-Based Data Selection Methods for Multimodal Contrastive Learning.
CoRR
Yiping Wang, Yifang Chen, Wendan Yan, Alex Fang, Wenjing Zhou, Kevin Jamieson, Simon Shaolei Du
2024 J jnl
Cost-Effective Proxy Reward Model Construction with On-Policy and Active Learning.
CoRR
Yifang Chen, Shuohang Wang, Ziyi Yang, Hiteshi Sharma, Nikos Karampatziakis, Donghan Yu, Kevin Jamieson, Simon Shaolei Du, Yelong Shen
2024 A conf
Fair Active Learning in Low-Data Regimes.
UAI
Romain Camilleri, Andrew Wagenmaker, Jamie Morgenstern, Lalit Jain, Kevin Jamieson
2024 A* conf
Humor in AI: Massive Scale Crowd-Sourced Preferences and Benchmarks for Cartoon Captioning.
NeurIPS
Jifan Zhang, Lalit K. Jain, Yang Guo, Jiayi Chen, Kuan Lok Zhou, Siddharth Suresh, Andrew Wagenmaker, Scott Sievert, Timothy T. Rogers, Kevin Jamieson, Bob Mankoff, Robert Nowak
2024 J jnl
Humor in AI: Massive Scale Crowd-Sourced Preferences and Benchmarks for Cartoon Captioning.
CoRR
Jifan Zhang, Lalit K. Jain, Yang Guo, Jiayi Chen, Kuan Lok Zhou, Siddharth Suresh, Andrew Wagenmaker, Scott Sievert, Timothy T. Rogers, Kevin Jamieson, Robert Mankoff, Robert Nowak
2024 J jnl
LabelBench: A Comprehensive Framework for Benchmarking Adaptive Label-Efficient Learning.
J. Data-centric Mach. Learn. Res.
Jifan Zhang, Yifang Chen, Gregory Canal, Arnav Mohanty Das, Gantavya Bhatt, Stephen Mussmann, Yinglun Zhu, Jeff A. Bilmes, Simon Shaolei Du, Kevin Jamieson, Robert D. Nowak
2024 A conf
Near-Optimal Pure Exploration in Matrix Games: A Generalization of Stochastic Bandits & Dueling Bandits.
AISTATS
Arnab Maiti, Ross Boczar, Kevin Jamieson, Lillian J. Ratliff
2024 A* conf
Nearly Minimax Optimal Submodular Maximization with Bandit Feedback.
NeurIPS
Artin Tajdini, Lalit Jain, Kevin Jamieson
2024 A conf
Optimal Exploration is no harder than Thompson Sampling.
AISTATS
Zhaoqi Li, Kevin Jamieson, Lalit Jain
2024 A* conf
Overcoming the Sim-to-Real Gap: Leveraging Simulation to Learn to Explore for Real-World RL.
NeurIPS
Andrew Wagenmaker, Kevin Huang, Liyiming Ke, Kevin Jamieson, Abhishek Gupta
2024 J jnl
Overcoming the Sim-to-Real Gap: Leveraging Simulation to Learn to Explore for Real-World RL.
CoRR
Andrew Wagenmaker, Kevin Huang, Liyiming Ke, Byron Boots, Kevin Jamieson, Abhishek Gupta
2024 A* conf
Sample Complexity Reduction via Policy Difference Estimation in Tabular Reinforcement Learning.
NeurIPS
Adhyyan Narang, Andrew Wagenmaker, Lillian J. Ratliff, Kevin Jamieson
2024 J jnl
Sample Complexity Reduction via Policy Difference Estimation in Tabular Reinforcement Learning.
CoRR
Adhyyan Narang, Andrew Wagenmaker, Lillian J. Ratliff, Kevin Jamieson
2024 J jnl
Variance Alignment Score: A Simple But Tough-to-Beat Data Selection Method for Multimodal Contrastive Learning.
CoRR
Yiping Wang, Yifang Chen, Wendan Yan, Kevin Jamieson, Simon Shaolei Du
2023 J jnl
A/B Testing and Best-arm Identification for Linear Bandits with Robustness to Non-stationarity.
CoRR
Zhihan Xiong, Romain Camilleri, Maryam Fazel, Lalit Jain, Kevin Jamieson
2023 J jnl
Active Representation Learning for General Task Space with Applications in Robotics.
CoRR
Yifang Chen, Yingbing Huang, Simon S. Du, Kevin Jamieson, Guanya Shi
2023 A* conf
Active representation learning for general task space with applications in robotics.
NeurIPS
Yifang Chen, Yingbing Huang, Simon S. Du, Kevin Jamieson, Guanya Shi
2023 — conf
Demonstrating Large-Scale Package Manipulation via Learned Metrics of Pick Success.
Robotics: Science and Systems
Shuai Li, Azarakhsh Keipour, Kevin Jamieson, Nicolas Hudson, Charles Swan, Kostas E. Bekris
2023 J jnl
Fair Active Learning in Low-Data Regimes.
CoRR
Romain Camilleri, Andrew Wagenmaker, Jamie Morgenstern, Lalit Jain, Kevin Jamieson
2023 A* conf
Improved Active Multi-Task Representation Learning via Lasso.
ICML
Yiping Wang, Yifang Chen, Kevin Jamieson, Simon Shaolei Du
2023 J jnl
Improved Active Multi-Task Representation Learning via Lasso.
CoRR
Yiping Wang, Yifang Chen, Kevin Jamieson, Simon S. Du
2023 A conf
Instance-dependent Sample Complexity Bounds for Zero-sum Matrix Games.
AISTATS
Arnab Maiti, Kevin Jamieson, Lillian J. Ratliff
2023 J jnl
Instance-dependent Sample Complexity Bounds for Zero-sum Matrix Games.
CoRR
Arnab Maiti, Kevin Jamieson, Lillian J. Ratliff
2023 J jnl
LabelBench: A Comprehensive Framework for Benchmarking Label-Efficient Learning.
CoRR
Jifan Zhang, Yifang Chen, Gregory Canal, Stephen Mussmann, Yinglun Zhu, Simon Shaolei Du, Kevin Jamieson, Robert D. Nowak
2023 J jnl
Large-Scale Package Manipulation via Learned Metrics of Pick Success.
CoRR
Shuai Li, Azarakhsh Keipour, Kevin Jamieson, Nicolas Hudson, Charles Swan, Kostas E. Bekris
2023 J jnl
Logarithmic Regret for Matrix Games against an Adversary with Noisy Bandit Feedback.
CoRR
Arnab Maiti, Kevin Jamieson, Lillian J. Ratliff
2023 J jnl
Minimax Optimal Submodular Optimization with Bandit Feedback.
CoRR
Artin Tajdini, Lalit Jain, Kevin Jamieson
2023 J jnl
Near-Optimal Pure Exploration in Matrix Games: A Generalization of Stochastic Bandits & Dueling Bandits.
CoRR
Arnab Maiti, Ross Boczar, Kevin Jamieson, Lillian J. Ratliff
2023 A* conf
Optimal Exploration for Model-Based RL in Nonlinear Systems.
NeurIPS
Andrew Wagenmaker, Guanya Shi, Kevin Jamieson
2023 J jnl
Optimal Exploration for Model-Based RL in Nonlinear Systems.
CoRR
Andrew Wagenmaker, Guanya Shi, Kevin Jamieson
2023 J jnl
Optimal Exploration is no harder than Thompson Sampling.
CoRR
Zhaoqi Li, Kevin Jamieson, Lalit Jain
2023 J jnl
Pick Planning Strategies for Large-Scale Package Manipulation.
CoRR
Shuai Li, Azarakhsh Keipour, Kevin Jamieson, Nicolas Hudson, Sicong Zhao, Charles Swan, Kostas E. Bekris
2023 J jnl
Query-Efficient Algorithms to Find the Unique Nash Equilibrium in a Two-Player Zero-Sum Matrix Game.
CoRR
Arnab Maiti, Ross Boczar, Kevin Jamieson, Lillian J. Ratliff
2022 A* conf
Active Learning with Safety Constraints.
NeurIPS
Romain Camilleri, Andrew Wagenmaker, Jamie H. Morgenstern, Lalit Jain, Kevin Jamieson
2022 J jnl
Active Learning with Safety Constraints.
CoRR
Romain Camilleri, Andrew Wagenmaker, Jamie Morgenstern, Lalit Jain, Kevin Jamieson
2022 A* conf
Active Multi-Task Representation Learning.
ICML
Yifang Chen, Kevin Jamieson, Simon S. Du
2022 J jnl
Active Multi-Task Representation Learning.
CoRR
Yifang Chen, Simon S. Du, Kevin Jamieson
2022 A conf
Best Arm Identification with Safety Constraints.
AISTATS
Zhenlin Wang, Andrew J. Wagenmaker, Kevin Jamieson
2022 A* conf
Beyond No Regret: Instance-Dependent PAC Reinforcement Learning.
COLT
Andrew J. Wagenmaker, Max Simchowitz, Kevin Jamieson
2022 A* conf
First-Order Regret in Reinforcement Learning with Linear Function Approximation: A Robust Estimation Approach.
ICML
Andrew J. Wagenmaker, Yifang Chen, Max Simchowitz, Simon S. Du, Kevin Jamieson
2022 A conf
Identifying New Podcasts with High General Appeal Using a Pure Exploration Infinitely-Armed Bandit Strategy.
RecSys
Maryam Aziz, Jesse Anderton, Kevin Jamieson, Alice Wang, Hugues Bouchard, Javed A. Aslam
2022 A* conf
Instance-Dependent Near-Optimal Policy Identification in Linear MDPs via Online Experiment Design.
NeurIPS
Andrew Wagenmaker, Kevin Jamieson
2022 J jnl
Instance-Dependent Near-Optimal Policy Identification in Linear MDPs via Online Experiment Design.
CoRR
Andrew Wagenmaker, Kevin Jamieson
2022 A* conf
Instance-optimal PAC Algorithms for Contextual Bandits.
NeurIPS
Zhaoqi Li, Lillian J. Ratliff, Houssam Nassif, Kevin Jamieson, Lalit Jain
2022 J jnl
Instance-optimal PAC Algorithms for Contextual Bandits.
CoRR
Zhaoqi Li, Lillian J. Ratliff, Houssam Nassif, Kevin Jamieson, Lalit Jain
2022 A conf
Nearly Optimal Algorithms for Level Set Estimation.
AISTATS
Blake Mason, Lalit K. Jain, Subhojyoti Mukherjee, Romain Camilleri, Kevin Jamieson, Robert D. Nowak
2022 A* conf
Reward-Free RL is No Harder Than Reward-Aware RL in Linear Markov Decision Processes.
ICML
Andrew J. Wagenmaker, Yifang Chen, Max Simchowitz, Simon S. Du, Kevin Jamieson
2022 J jnl
Reward-Free RL is No Harder Than Reward-Aware RL in Linear Markov Decision Processes.
CoRR
Andrew Wagenmaker, Yifang Chen, Max Simchowitz, Simon S. Du, Kevin Jamieson
2022 J jnl
Sample-efficient identification of high-dimensional antibiotic synergy with a normalized diagonal sampling design.
PLoS Comput. Biol.
Jennifer Brennan, Lalit Jain, Sofia Garman, Ann E. Donnelly, Erik Scott Wright, Kevin Jamieson
2021 J jnl
Best Arm Identification with Safety Constraints.
CoRR
Zhenlin Wang, Andrew Wagenmaker, Kevin Jamieson
2021 J jnl
Beyond No Regret: Instance-Dependent PAC Reinforcement Learning.
CoRR
Andrew Wagenmaker, Max Simchowitz, Kevin Jamieson
2021 A* conf
Corruption Robust Active Learning.
NeurIPS
Yifang Chen, Simon S. Du, Kevin Jamieson
2021 J jnl
Corruption Robust Active Learning.
CoRR
Yifang Chen, Simon S. Du, Kevin Jamieson
2021 A conf
Experimental Design for Regret Minimization in Linear Bandits.
AISTATS
Andrew Wagenmaker, Julian Katz-Samuels, Kevin Jamieson
2021 J jnl
First-Order Regret in Reinforcement Learning with Linear Function Approximation: A Robust Estimation Approach.
CoRR
Andrew Wagenmaker, Yifang Chen, Max Simchowitz, Simon S. Du, Kevin Jamieson
2021 J jnl
High-Dimensional Experimental Design and Kernel Bandits.
CoRR
Romain Camilleri, Julian Katz-Samuels, Kevin Jamieson
2021 A* conf
High-dimensional Experimental Design and Kernel Bandits.
ICML
Romain Camilleri, Kevin Jamieson, Julian Katz-Samuels
2021 A* conf
Improved Algorithms for Agnostic Pool-based Active Classification.
ICML
Julian Katz-Samuels, Jifan Zhang, Lalit Jain, Kevin Jamieson
2021 J jnl
Improved Algorithms for Agnostic Pool-based Active Classification.
CoRR
Julian Katz-Samuels, Jifan Zhang, Lalit Jain, Kevin Jamieson
2021 A* conf
Improved Corruption Robust Algorithms for Episodic Reinforcement Learning.
ICML
Yifang Chen, Simon S. Du, Kevin Jamieson
2021 J jnl
Improved Corruption Robust Algorithms for Episodic Reinforcement Learning.
CoRR
Yifang Chen, Simon S. Du, Kevin Jamieson
2021 A* conf
Leveraging Post Hoc Context for Faster Learning in Bandit Settings with Applications in Robot-Assisted Feeding.
ICRA
Ethan K. Gordon, Sumegh Roychowdhury, Tapomayukh Bhattacharjee, Kevin Jamieson, Siddhartha S. Srinivasa
2021 J jnl
Nearly Optimal Algorithms for Level Set Estimation.
CoRR
Blake Mason, Romain Camilleri, Subhojyoti Mukherjee, Kevin Jamieson, Robert D. Nowak, Lalit K. Jain
2021 A* conf
Practical, Provably-Correct Interactive Learning in the Realizable Setting: The Power of True Believers.
NeurIPS
Julian Katz-Samuels, Blake Mason, Kevin Jamieson, Robert Nowak
2021 J jnl
Practical, Provably-Correct Interactive Learning in the Realizable Setting: The Power of True Believers.
CoRR
Julian Katz-Samuels, Blake Mason, Kevin Jamieson, Robert D. Nowak
2021 A* conf
Selective Sampling for Online Best-arm Identification.
NeurIPS
Romain Camilleri, Zhihan Xiong, Maryam Fazel, Lalit Jain, Kevin Jamieson
2021 J jnl
Selective Sampling for Online Best-arm Identification.
CoRR
Romain Camilleri, Zhihan Xiong, Maryam Fazel, Lalit Jain, Kevin Jamieson
2021 A* conf
Task-Optimal Exploration in Linear Dynamical Systems.
ICML
Andrew J. Wagenmaker, Max Simchowitz, Kevin Jamieson
2021 J jnl
Task-Optimal Exploration in Linear Dynamical Systems.
CoRR
Andrew Wagenmaker, Max Simchowitz, Kevin Jamieson
2020 J jnl
A New Perspective on Pool-Based Active Classification and False-Discovery Control.
CoRR
Lalit Jain, Kevin Jamieson
2020 — conf
A System for Massively Parallel Hyperparameter Tuning.
MLSys
Liam Li, Kevin Jamieson, Afshin Rostamizadeh, Ekaterina Gonina, Jonathan Ben-tzur, Moritz Hardt, Benjamin Recht, Ameet Talwalkar
2020 A* conf
Active Learning for Identification of Linear Dynamical Systems.
COLT
Andrew Wagenmaker, Kevin Jamieson
2020 J jnl
Active Learning for Identification of Linear Dynamical Systems.
CoRR
Andrew Wagenmaker, Kevin Jamieson
2020 A* conf
An Empirical Process Approach to the Union Bound: Practical Algorithms for Combinatorial and Linear Bandits.
NeurIPS
Julian Katz-Samuels, Lalit Jain, Zohar S. Karnin, Kevin Jamieson
2020 J jnl
An Empirical Process Approach to the Union Bound: Practical Algorithms for Combinatorial and Linear Bandits.
CoRR
Julian Katz-Samuels, Lalit Jain, Zohar S. Karnin, Kevin Jamieson
2020 A* conf
Estimating the Number and Effect Sizes of Non-null Hypotheses.
ICML
Jennifer Brennan, Ramya Korlakai Vinayak, Kevin Jamieson
2020 J jnl
Estimating the number and effect sizes of non-null hypotheses.
CoRR
Jennifer Brennan, Ramya Korlakai Vinayak, Kevin Jamieson
2020 J jnl
Experimental Design for Regret Minimization in Linear Bandits.
CoRR
Andrew Wagenmaker, Julian Katz-Samuels, Kevin Jamieson
2020 J jnl
Learning to Actively Learn: A Robust Approach.
CoRR
Jifan Zhang, Kevin Jamieson
2020 J jnl
Leveraging Post Hoc Context for Faster Learning in Bandit Settings with Applications in Robot-Assisted Feeding.
CoRR
Ethan K. Gordon, Sumegh Roychowdhury, Tapomayukh Bhattacharjee, Kevin Jamieson, Siddhartha S. Srinivasa
2020 A conf
Mosaic: A Sample-Based Database System for Open World Query Processing.
CIDR
Laurel J. Orr, Samuel K. Ainsworth, Kevin Jamieson, Walter Cai, Magdalena Balazinska, Dan Suciu
2020 A conf
The True Sample Complexity of Identifying Good Arms.
AISTATS
Julian Katz-Samuels, Kevin Jamieson
2019 A* conf
A New Perspective on Pool-Based Active Classification and False-Discovery Control.
NeurIPS
Lalit Jain, Kevin Jamieson
2019 J jnl
Exploiting Reuse in Pipeline-Aware Hyperparameter Tuning.
CoRR
Liam Li, Evan Randall Sparks, Kevin Jamieson, Ameet Talwalkar
2019 J jnl
Mosaic: A Sample-Based Database System for Open World Query Processing.
CoRR
Laurel J. Orr, Samuel K. Ainsworth, Walter Cai, Kevin Jamieson, Magda Balazinska, Dan Suciu
2019 A* conf
Non-Asymptotic Gap-Dependent Regret Bounds for Tabular MDPs.
NeurIPS
Max Simchowitz, Kevin Jamieson
2019 J jnl
Non-Asymptotic Gap-Dependent Regret Bounds for Tabular MDPs.
CoRR
Max Simchowitz, Kevin Jamieson
2019 A* conf
Sequential Experimental Design for Transductive Linear Bandits.
NeurIPS
Tanner Fiez, Lalit Jain, Kevin Jamieson, Lillian J. Ratliff
2019 J jnl
Sequential Experimental Design for Transductive Linear Bandits.
CoRR
Tanner Fiez, Lalit Jain, Kevin Jamieson, Lillian J. Ratliff
2019 J jnl
SysML: The New Frontier of Machine Learning Systems.
CoRR
Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric S. Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros G. Dimakis, Pradeep Dubey, Charles Elkan, Grigori Fursin, Gregory R. Ganger, Lise Getoor, Phillip B. Gibbons, Garth A. Gibson, Joseph E. Gonzalez, Justin Gottschlich, Song Han, Kim M. Hazelwood, Furong Huang, Martin Jaggi, Kevin Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konecný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Jing Li, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Gordon Murray, Dimitris S. Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan Randall Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric P. Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar
2019 J jnl
The True Sample Complexity of Identifying Good Arms.
CoRR
Julian Katz-Samuels, Kevin Jamieson
2018 J jnl
A Bandit Approach to Multiple Testing with False Discovery Control.
CoRR
Kevin Jamieson, Lalit Jain
2018 A* conf
A Bandit Approach to Sequential Experimental Design with False Discovery Control.
NeurIPS
Kevin Jamieson, Lalit Jain
2018 J jnl
Adaptive Sampling for Convex Regression.
CoRR
Max Simchowitz, Kevin Jamieson, Jordan W. Suchow, Thomas L. Griffiths
2018 A* conf
Firing Bandits: Optimizing Crowdfunding.
ICML
Lalit Jain, Kevin Jamieson
2018 J jnl
Massively Parallel Hyperparameter Tuning.
CoRR
Liam Li, Kevin Jamieson, Afshin Rostamizadeh, Ekaterina Gonina, Moritz Hardt, Benjamin Recht, Ameet Talwalkar
2017 — conf
A framework for Multi-A(rmed)/B(andit) Testing with Online FDR Control.
NIPS
Fanny Yang, Aaditya Ramdas, Kevin Jamieson, Martin J. Wainwright
2017 J jnl
A framework for Multi-A(rmed)/B(andit) testing with online FDR control.
CoRR
Fanny Yang, Aaditya Ramdas, Kevin Jamieson, Martin J. Wainwright
2017 A* conf
Comparing human-centric and robot-centric sampling for robot deep learning from demonstrations.
ICRA
Michael Laskey, Caleb Chuck, Jonathan Lee, Jeffrey Mahler, Sanjay Krishnan, Kevin Jamieson, Anca D. Dragan, Ken Goldberg
2017 J jnl
Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization.
J. Mach. Learn. Res.
Lisha Li, Kevin Jamieson, Giulia DeSalvo, Afshin Rostamizadeh, Ameet Talwalkar
2017 — conf
Hyperband: Bandit-Based Configuration Evaluation for Hyperparameter Optimization.
ICLR (Poster)
Lisha Li, Kevin Jamieson, Giulia DeSalvo, Afshin Rostamizadeh, Ameet Talwalkar
2017 — conf
NEXT: A system to easily connect crowdsourcing and adaptive data collection.
SciPy
Scott Sievert, Daniel Ross, Lalit K. Jain, Kevin Jamieson, Robert Nowak, Robert Mankoff
2017 A* conf
The Simulator: Understanding Adaptive Sampling in the Moderate-Confidence Regime.
COLT
Max Simchowitz, Kevin Jamieson, Benjamin Recht
2017 J jnl
The Simulator: Understanding Adaptive Sampling in the Moderate-Confidence Regime.
CoRR
Max Simchowitz, Kevin Jamieson, Benjamin Recht
2016 J jnl
Best-of-K Bandits.
CoRR
Max Simchowitz, Kevin Jamieson, Benjamin Recht
2016 A* conf
Best-of-K-bandits.
COLT
Max Simchowitz, Kevin Jamieson, Benjamin Recht
2016 J jnl
Comparing Human-Centric and Robot-Centric Sampling for Robot Deep Learning from Demonstrations.
CoRR
Michael Laskey, Caleb Chuck, Jonathan Lee, Jeffrey Mahler, Sanjay Krishnan, Kevin Jamieson, Anca D. Dragan, Kenneth Y. Goldberg
2016 J jnl
Efficient Hyperparameter Optimization and Infinitely Many Armed Bandits.
CoRR
Lisha Li, Kevin Jamieson, Giulia DeSalvo, Afshin Rostamizadeh, Ameet Talwalkar
2016 — conf
Finite Sample Prediction and Recovery Bounds for Ordinal Embedding.
NIPS
Lalit K. Jain, Kevin Jamieson, Robert D. Nowak
2016 J jnl
Finite Sample Prediction and Recovery Bounds for Ordinal Embedding.
CoRR
Lalit K. Jain, Kevin Jamieson, Robert D. Nowak
2016 A conf
Non-stochastic Best Arm Identification and Hyperparameter Optimization.
AISTATS
Kevin Jamieson, Ameet Talwalkar
2016 J jnl
On the Detection of Mixture Distributions with applications to the Most Biased Coin Problem.
CoRR
Kevin Jamieson, Daniel Haas, Benjamin Recht
2016 — conf
The Power of Adaptivity in Identifying Statistical Alternatives.
NIPS
Kevin Jamieson, Daniel Haas, Benjamin Recht
2016 A conf
Top Arm Identification in Multi-Armed Bandits with Batch Arm Pulls.
AISTATS
Kwang-Sung Jun, Kevin Jamieson, Robert D. Nowak, Xiaojin Zhu
2015 — conf
NEXT: A System for Real-World Development, Evaluation, and Application of Active Learning.
NIPS
Kevin Jamieson, Lalit K. Jain, Chris Fernandez, Nicholas J. Glattard, Robert D. Nowak
2015 J jnl
Non-stochastic Best Arm Identification and Hyperparameter Optimization.
CoRR
Kevin Jamieson, Ameet Talwalkar
2015 A conf
Sparse Dueling Bandits.
AISTATS
Kevin Jamieson, Sumeet Katariya, Atul Deshpande, Robert D. Nowak
2015 J jnl
Sparse Dueling Bandits.
CoRR
Kevin Jamieson, Sumeet Katariya, Atul Deshpande, Robert D. Nowak
2014 Misc conf
Best-arm identification algorithms for multi-armed bandits in the fixed confidence setting.
CISS
Kevin Jamieson, Robert D. Nowak
2014 A* conf
lil' UCB : An Optimal Exploration Algorithm for Multi-Armed Bandits.
COLT
Kevin Jamieson, Matthew Malloy, Robert D. Nowak, Sébastien Bubeck
2013 J jnl
On Finding the Largest Mean Among Many.
CoRR
Kevin Jamieson, Matthew Malloy, Robert D. Nowak, Sébastien Bubeck
2013 J jnl
lil' UCB : An Optimal Exploration Algorithm for Multi-Armed Bandits.
CoRR
Kevin Jamieson, Matthew Malloy, Robert D. Nowak, Sébastien Bubeck
2011 J jnl
Channel-Robust Classifiers.
IEEE Trans. Signal Process.
Hyrum S. Anderson, Maya R. Gupta, Eric Swanson, Kevin Jamieson
2010 Misc conf
Training a support vector machine to classify signals in a real environment given clean training data.
ICASSP
Kevin Jamieson, Maya R. Gupta, Eric Swanson, Hyrum S. Anderson