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08/17/2023
Model-Free Algorithm with Improved Sample Efficiency for Zero-Sum Markov Games
The problem of two-player zero-sum Markov games has recently attracted i...
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06/24/2023
Offline Policy Evaluation for Reinforcement Learning with Adaptively Collected Data
Developing theoretical guarantees on the sample complexity of offline RL...
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06/01/2023
Non-stationary Reinforcement Learning under General Function Approximation
General function approximation is a powerful tool to handle large state ...
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05/21/2023
TheoremQA: A Theorem-driven Question Answering dataset
The recent LLMs like GPT-4 and PaLM-2 have made tremendous progress in s...
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05/08/2023
Interactive Concept Learning for Uncovering Latent Themes in Large Text Collections
Experts across diverse disciplines are often interested in making sense ...
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04/27/2023
Neutral Atom Quantum Computing Hardware: Performance and End-User Perspective
We present an industrial end-user perspective on the current state of qu...
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02/26/2023
No-Regret Linear Bandits beyond Realizability
We study linear bandits when the underlying reward function is not linea...
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02/24/2023
Logarithmic Switching Cost in Reinforcement Learning beyond Linear MDPs
In many real-life reinforcement learning (RL) problems, deploying new po...
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01/14/2023
Who Should I Trust: AI or Myself? Leveraging Human and AI Correctness Likelihood to Promote Appropriate Trust in AI-Assisted Decision-Making
In AI-assisted decision-making, it is critical for human decision-makers...
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11/23/2022
On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation
Sample-efficient offline reinforcement learning (RL) with linear functio...
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10/03/2022
Offline Reinforcement Learning with Differentiable Function Approximation is Provably Efficient
Offline reinforcement learning, which aims at optimizing sequential deci...
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06/13/2022
Why Quantization Improves Generalization: NTK of Binary Weight Neural Networks
Quantized neural networks have drawn a lot of attention as they reduce t...
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06/10/2022
Offline Stochastic Shortest Path: Learning, Evaluation and Towards Optimality
Goal-oriented Reinforcement Learning, where the agent needs to reach the...
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05/03/2022
A Holistic Framework for Analyzing the COVID-19 Vaccine Debate
The Covid-19 pandemic has led to infodemic of low quality information le...
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03/11/2022
Near-optimal Offline Reinforcement Learning with Linear Representation: Leveraging Variance Information with Pessimism
Offline reinforcement learning, which seeks to utilize offline/historica...
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02/13/2022
Sample-Efficient Reinforcement Learning with loglog(T) Switching Cost
We study the problem of reinforcement learning (RL) with low (policy) sw...
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10/17/2021
Towards Instance-Optimal Offline Reinforcement Learning with Pessimism
We study the offline reinforcement learning (offline RL) problem, where ...
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05/13/2021
Optimal Uniform OPE and Model-based Offline Reinforcement Learning in Time-Homogeneous, Reward-Free and Task-Agnostic Settings
This work studies the statistical limits of uniform convergence for offl...
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02/02/2021
Near-Optimal Offline Reinforcement Learning via Double Variance Reduction
We consider the problem of offline reinforcement learning (RL) – a well-...
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07/07/2020
Near Optimal Provable Uniform Convergence in Off-Policy Evaluation for Reinforcement Learning
The Off-Policy Evaluation aims at estimating the performance of target p...
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01/29/2020
Asymptotically Efficient Off-Policy Evaluation for Tabular Reinforcement Learning
We consider the problem of off-policy evaluation for reinforcement learn...
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07/23/2019
Shared Generative Latent Representation Learning for Multi-view Clustering
Clustering multi-view data has been a fundamental research topic in the ...
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10/23/2018
Working in Pairs: Understanding the Effects of Worker Interactions in Crowdwork
Crowdsourcing has gained popularity as a tool to harness human brain pow...
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08/30/2016
Low-rank Multi-view Clustering in Third-Order Tensor Space
The plenty information from multiple views data as well as the complemen...
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01/27/2016
Neighborhood Preserved Sparse Representation for Robust Classification on Symmetric Positive Definite Matrices
Due to its promising classification performance, sparse representation b...
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01/04/2016
Kernel Sparse Subspace Clustering on Symmetric Positive Definite Manifolds
Sparse subspace clustering (SSC), as one of the most successful subspace...
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06/30/2015
