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06/16/2023
LabelBench: A Comprehensive Framework for Benchmarking Label-Efficient Learning
Labeled data are critical to modern machine learning applications, but o...
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06/15/2023
Active Representation Learning for General Task Space with Applications in Robotics
Representation learning based on multi-task pretraining has become a pow...
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06/05/2023
Improved Active Multi-Task Representation Learning via Lasso
To leverage the copious amount of data from source tasks and overcome th...
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11/04/2022
Improved Adaptive Algorithm for Scalable Active Learning with Weak Labeler
Active learning with strong and weak labelers considers a practical sett...
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05/05/2022
A Deep Bayesian Bandits Approach for Anticancer Therapy: Exploration via Functional Prior
Learning personalized cancer treatment with machine learning holds great...
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02/02/2022
Active Multi-Task Representation Learning
To leverage the power of big data from source tasks and overcome the sca...
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01/26/2022
Reward-Free RL is No Harder Than Reward-Aware RL in Linear Markov Decision Processes
Reward-free reinforcement learning (RL) considers the setting where the ...
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12/07/2021
First-Order Regret in Reinforcement Learning with Linear Function Approximation: A Robust Estimation Approach
Obtaining first-order regret bounds – regret bounds scaling not as the w...
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06/21/2021
Corruption Robust Active Learning
We conduct theoretical studies on streaming-based active learning for bi...
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02/13/2021
Improved Corruption Robust Algorithms for Episodic Reinforcement Learning
We study episodic reinforcement learning under unknown adversarial corru...
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06/01/2020
More Practical and Adaptive Algorithms for Online Quantum State Learning
Online quantum state learning is a recently proposed problem by Aaronson...
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12/13/2019
Fair Contextual Multi-Armed Bandits: Theory and Experiments
When an AI system interacts with multiple users, it frequently needs to ...
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12/03/2019
Online and Bandit Algorithms for Nonstationary Stochastic Saddle-Point Optimization
Saddle-point optimization problems are an important class of optimizatio...
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06/30/2019
Reinforcement Learning with Fairness Constraints for Resource Distribution in Human-Robot Teams
Much work in robotics and operations research has focused on optimal res...
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02/03/2019
