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07/06/2023
Provably Efficient Iterated CVaR Reinforcement Learning with Function Approximation
Risk-sensitive reinforcement learning (RL) aims to optimize policies tha...
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07/04/2023
Beyond Conservatism: Diffusion Policies in Offline Multi-agent Reinforcement Learning
We present a novel Diffusion Offline Multi-agent Model (DOM2) for offlin...
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03/03/2023
Queue Scheduling with Adversarial Bandit Learning
In this paper, we study scheduling of a queueing system with zero knowle...
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03/03/2023
RePreM: Representation Pre-training with Masked Model for Reinforcement Learning
Inspired by the recent success of sequence modeling in RL and the use of...
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03/02/2023
Why (and When) does Local SGD Generalize Better than SGD?
Local SGD is a communication-efficient variant of SGD for large-scale tr...
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02/19/2023
Stochastic Generative Flow Networks
Generative Flow Networks (or GFlowNets for short) are a family of probab...
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02/13/2023
Provably Safe Reinforcement Learning with Step-wise Violation Constraints
In this paper, we investigate a novel safe reinforcement learning proble...
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02/09/2023
Multi-task Representation Learning for Pure Exploration in Linear Bandits
Despite the recent success of representation learning in sequential deci...
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11/16/2022
Dueling Bandits: From Two-dueling to Multi-dueling
We study a general multi-dueling bandit problem, where an agent compares...
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10/07/2022
Generative Augmented Flow Networks
The Generative Flow Network is a probabilistic framework where an agent ...
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08/30/2022
Effective Multi-User Delay-Constrained Scheduling with Deep Recurrent Reinforcement Learning
Multi-user delay constrained scheduling is important in many real-world ...
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06/23/2022
Nearly Minimax Optimal Reinforcement Learning with Linear Function Approximation
We study reinforcement learning with linear function approximation where...
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06/18/2022
Provable Generalization of Overparameterized Meta-learning Trained with SGD
Despite the superior empirical success of deep meta-learning, theoretica...
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06/06/2022
Risk-Sensitive Reinforcement Learning: Iterated CVaR and the Worst Path
In this paper, we study a novel episodic risk-sensitive Reinforcement Le...
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05/30/2022
RLx2: Training a Sparse Deep Reinforcement Learning Model from Scratch
Training deep reinforcement learning (DRL) models usually requires high ...
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04/19/2022
Network Topology Optimization via Deep Reinforcement Learning
Topology impacts important network performance metrics, including link u...
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03/23/2022
Modality Competition: What Makes Joint Training of Multi-modal Network Fail in Deep Learning? (Provably)
Despite the remarkable success of deep multi-modal learning in practice,...
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01/28/2022
Adaptive Best-of-Both-Worlds Algorithm for Heavy-Tailed Multi-Armed Bandits
In this paper, we generalize the concept of heavy-tailed multi-armed ban...
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11/22/2021
Plan Better Amid Conservatism: Offline Multi-Agent Reinforcement Learning with Actor Rectification
The idea of conservatism has led to significant progress in offline rein...
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11/15/2021
Simultaneously Achieving Sublinear Regret and Constraint Violations for Online Convex Optimization with Time-varying Constraints
In this paper, we develop a novel virtual-queue-based online algorithm f...
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10/29/2021
Collaborative Pure Exploration in Kernel Bandit
In this paper, we formulate a Collaborative Pure Exploration in Kernel B...
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10/26/2021
Scale-Free Adversarial Multi-Armed Bandit with Arbitrary Feedback Delays
We consider the Scale-Free Adversarial Multi Armed Bandit (MAB) problem ...
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06/16/2021
Banker Online Mirror Descent
We propose Banker-OMD, a novel framework generalizing the classical Onli...
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06/08/2021
What Makes Multimodal Learning Better than Single (Provably)
The world provides us with data of multiple modalities. Intuitively, mod...
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06/08/2021
Fast Federated Learning in the Presence of Arbitrary Device Unavailability
Federated Learning (FL) coordinates with numerous heterogeneous devices ...
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06/08/2021
The best of both worlds: stochastic and adversarial episodic MDPs with unknown transition
We consider the best-of-both-worlds problem for learning an episodic Mar...
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03/22/2021
Regularized Softmax Deep Multi-Agent Q-Learning
Tackling overestimation in Q-learning is an important problem that has b...
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02/24/2021
Continuous Mean-Covariance Bandits
Existing risk-aware multi-armed bandit models typically focus on risk me...
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12/14/2020
A One-Size-Fits-All Solution to Conservative Bandit Problems
In this paper, we study a family of conservative bandit problems (CBPs) ...
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12/13/2020
Adaptive Algorithms for Multi-armed Bandit with Composite and Anonymous Feedback
We study the multi-armed bandit (MAB) problem with composite and anonymo...
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11/05/2020
Restless-UCB, an Efficient and Low-complexity Algorithm for Online Restless Bandits
We study the online restless bandit problem, where the state of each arm...
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10/19/2020
Softmax Deep Double Deterministic Policy Gradients
A widely-used actor-critic reinforcement learning algorithm for continuo...
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06/23/2020
Combinatorial Pure Exploration of Dueling Bandit
In this paper, we study combinatorial pure exploration for dueling bandi...
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06/11/2020
Distributed Reinforcement Learning in Multi-Agent Networked Systems
We study distributed reinforcement learning (RL) for a network of agents...
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06/11/2020
Exploration by Maximizing Rényi Entropy for Zero-Shot Meta RL
Exploring the transition dynamics is essential to the success of reinfor...
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11/11/2019
Multi-Path Policy Optimization
Recent years have witnessed a tremendous improvement of deep reinforceme...
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03/14/2019
Reinforcement Learning with Dynamic Boltzmann Softmax Updates
Value function estimation is an important task in reinforcement learning...
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11/05/2018
Multi-armed Bandits with Compensation
We propose and study the known-compensation multi-arm bandit (KCMAB) pro...
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05/25/2018
A New Analysis of Variance Reduced Stochastic Proximal Methods for Composite Optimization with Serial and Asynchronous Realizations
We provide a comprehensive analysis of stochastic variance reduced gradi...
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05/09/2018
Loyalty Programs in the Sharing Economy: Optimality and Competition
Loyalty programs are important tools for sharing platforms seeking to gr...
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05/04/2018
Beyond the Click-Through Rate: Web Link Selection with Multi-level Feedback
The web link selection problem is to select a small subset of web links ...
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02/13/2018
Rebalancing Dockless Bike Sharing Systems
Bike sharing provides an environment-friendly way for traveling and is b...
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12/15/2017
Timely-Throughput Optimal Scheduling with Prediction
Motivated by the increasing importance of providing delay-guaranteed ser...
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05/11/2017