Kevin G. Jamieson

Orcid: 0000-0003-2054-2985

Affiliations:
  • University of Washington, School of Computer Science, Seattle, WA, USA
  • University of California, Berkeley, Electrical Engineering and Computer Sciences Department, CA, USA
  • University of Wisconsin-Madison, Department of Electrical and Computer Engineering, WI, USA


According to our database1, Kevin G. Jamieson authored at least 85 papers between 2009 and 2025.

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Bibliography

2025
Unbiased Identification of Broadly Appealing Content Using a Pure Exploration Infinitely Armed Bandit Strategy.
Trans. Recomm. Syst., March, 2025

2024
Overcoming the Sim-to-Real Gap: Leveraging Simulation to Learn to Explore for Real-World RL.
CoRR, 2024

Cost-Effective Proxy Reward Model Construction with On-Policy and Active Learning.
CoRR, 2024

Humor in AI: Massive Scale Crowd-Sourced Preferences and Benchmarks for Cartoon Captioning.
CoRR, 2024

Sample Complexity Reduction via Policy Difference Estimation in Tabular Reinforcement Learning.
CoRR, 2024

CLIPLoss and Norm-Based Data Selection Methods for Multimodal Contrastive Learning.
CoRR, 2024

Variance Alignment Score: A Simple But Tough-to-Beat Data Selection Method for Multimodal Contrastive Learning.
CoRR, 2024

A/B Testing and Best-arm Identification for Linear Bandits with Robustness to Non-stationarity.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Near-Optimal Pure Exploration in Matrix Games: A Generalization of Stochastic Bandits & Dueling Bandits.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Optimal Exploration is no harder than Thompson Sampling.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

An Experimental Design Framework for Label-Efficient Supervised Finetuning of Large Language Models.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023
Fair Active Learning in Low-Data Regimes.
CoRR, 2023

Minimax Optimal Submodular Optimization with Bandit Feedback.
CoRR, 2023

Query-Efficient Algorithms to Find the Unique Nash Equilibrium in a Two-Player Zero-Sum Matrix Game.
CoRR, 2023

Pick Planning Strategies for Large-Scale Package Manipulation.
CoRR, 2023

Logarithmic Regret for Matrix Games against an Adversary with Noisy Bandit Feedback.
CoRR, 2023

LabelBench: A Comprehensive Framework for Benchmarking Label-Efficient Learning.
CoRR, 2023

Large-Scale Package Manipulation via Learned Metrics of Pick Success.
CoRR, 2023

Demonstrating Large-Scale Package Manipulation via Learned Metrics of Pick Success.
Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

Optimal Exploration for Model-Based RL in Nonlinear Systems.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Active representation learning for general task space with applications in robotics.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Improved Active Multi-Task Representation Learning via Lasso.
Proceedings of the International Conference on Machine Learning, 2023

Instance-dependent Sample Complexity Bounds for Zero-sum Matrix Games.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Sample-efficient identification of high-dimensional antibiotic synergy with a normalized diagonal sampling design.
PLoS Comput. Biol., 2022

Active Learning with Safety Constraints.
CoRR, 2022

Identifying New Podcasts with High General Appeal Using a Pure Exploration Infinitely-Armed Bandit Strategy.
Proceedings of the RecSys '22: Sixteenth ACM Conference on Recommender Systems, Seattle, WA, USA, September 18, 2022

Instance-Dependent Near-Optimal Policy Identification in Linear MDPs via Online Experiment Design.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Instance-optimal PAC Algorithms for Contextual Bandits.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Active Learning with Safety Constraints.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Reward-Free RL is No Harder Than Reward-Aware RL in Linear Markov Decision Processes.
Proceedings of the International Conference on Machine Learning, 2022

First-Order Regret in Reinforcement Learning with Linear Function Approximation: A Robust Estimation Approach.
Proceedings of the International Conference on Machine Learning, 2022

Active Multi-Task Representation Learning.
Proceedings of the International Conference on Machine Learning, 2022

Beyond No Regret: Instance-Dependent PAC Reinforcement Learning.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Best Arm Identification with Safety Constraints.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Nearly Optimal Algorithms for Level Set Estimation.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Practical, Provably-Correct Interactive Learning in the Realizable Setting: The Power of True Believers.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Corruption Robust Active Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Selective Sampling for Online Best-arm Identification.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Leveraging Post Hoc Context for Faster Learning in Bandit Settings with Applications in Robot-Assisted Feeding.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Task-Optimal Exploration in Linear Dynamical Systems.
Proceedings of the 38th International Conference on Machine Learning, 2021

Improved Algorithms for Agnostic Pool-based Active Classification.
Proceedings of the 38th International Conference on Machine Learning, 2021

Improved Corruption Robust Algorithms for Episodic Reinforcement Learning.
Proceedings of the 38th International Conference on Machine Learning, 2021

High-dimensional Experimental Design and Kernel Bandits.
Proceedings of the 38th International Conference on Machine Learning, 2021

Experimental Design for Regret Minimization in Linear Bandits.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Learning to Actively Learn: A Robust Approach.
CoRR, 2020

An Empirical Process Approach to the Union Bound: Practical Algorithms for Combinatorial and Linear Bandits.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

A System for Massively Parallel Hyperparameter Tuning.
Proceedings of the Third Conference on Machine Learning and Systems, 2020

Estimating the Number and Effect Sizes of Non-null Hypotheses.
Proceedings of the 37th International Conference on Machine Learning, 2020

Active Learning for Identification of Linear Dynamical Systems.
Proceedings of the Conference on Learning Theory, 2020

Mosaic: A Sample-Based Database System for Open World Query Processing.
Proceedings of the 10th Conference on Innovative Data Systems Research, 2020

The True Sample Complexity of Identifying Good Arms.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
SysML: The New Frontier of Machine Learning Systems.
CoRR, 2019

Exploiting Reuse in Pipeline-Aware Hyperparameter Tuning.
CoRR, 2019

Non-Asymptotic Gap-Dependent Regret Bounds for Tabular MDPs.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A New Perspective on Pool-Based Active Classification and False-Discovery Control.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Sequential Experimental Design for Transductive Linear Bandits.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018
Massively Parallel Hyperparameter Tuning.
CoRR, 2018

A Bandit Approach to Multiple Testing with False Discovery Control.
CoRR, 2018

Adaptive Sampling for Convex Regression.
CoRR, 2018

A Bandit Approach to Sequential Experimental Design with False Discovery Control.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Firing Bandits: Optimizing Crowdfunding.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization.
J. Mach. Learn. Res., 2017

NEXT: A system to easily connect crowdsourcing and adaptive data collection.
Proceedings of the 16th Python in Science Conference 2017, 2017

A framework for Multi-A(rmed)/B(andit) Testing with Online FDR Control.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Comparing human-centric and robot-centric sampling for robot deep learning from demonstrations.
Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Hyperband: Bandit-Based Configuration Evaluation for Hyperparameter Optimization.
Proceedings of the 5th International Conference on Learning Representations, 2017

The Simulator: Understanding Adaptive Sampling in the Moderate-Confidence Regime.
Proceedings of the 30th Conference on Learning Theory, 2017

2016
Efficient Hyperparameter Optimization and Infinitely Many Armed Bandits.
CoRR, 2016

On the Detection of Mixture Distributions with applications to the Most Biased Coin Problem.
CoRR, 2016

The Power of Adaptivity in Identifying Statistical Alternatives.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Finite Sample Prediction and Recovery Bounds for Ordinal Embedding.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Best-of-K-bandits.
Proceedings of the 29th Conference on Learning Theory, 2016

Top Arm Identification in Multi-Armed Bandits with Batch Arm Pulls.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Non-stochastic Best Arm Identification and Hyperparameter Optimization.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015
NEXT: A System for Real-World Development, Evaluation, and Application of Active Learning.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Sparse Dueling Bandits.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014
lil' UCB : An Optimal Exploration Algorithm for Multi-Armed Bandits.
Proceedings of The 27th Conference on Learning Theory, 2014

Best-arm identification algorithms for multi-armed bandits in the fixed confidence setting.
Proceedings of the 48th Annual Conference on Information Sciences and Systems, 2014

2013
On Finding the Largest Mean Among Many.
CoRR, 2013

2012
Query Complexity of Derivative-Free Optimization.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2011
Channel-Robust Classifiers.
IEEE Trans. Signal Process., 2011

Active Ranking using Pairwise Comparisons.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Low-dimensional embedding using adaptively selected ordinal data.
Proceedings of the 49th Annual Allerton Conference on Communication, 2011

2010
Training a support vector machine to classify signals in a real environment given clean training data.
Proceedings of the IEEE International Conference on Acoustics, 2010

2009
Sequential Bayesian estimation of the probability of detection for tracking.
Proceedings of the 12th International Conference on Information Fusion, 2009


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