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09/05/2023
Regret Analysis of Policy Gradient Algorithm for Infinite Horizon Average Reward Markov Decision Processes
In this paper, we consider an infinite horizon average reward Markov Dec...
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08/28/2023
Statistically Efficient Variance Reduction with Double Policy Estimation for Off-Policy Evaluation in Sequence-Modeled Reinforcement Learning
Offline reinforcement learning aims to utilize datasets of previously ga...
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07/21/2023
Scalable Multi-agent Covering Option Discovery based on Kronecker Graphs
Covering skill (a.k.a., option) discovery has been developed to improve ...
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07/08/2023
Noisy Tensor Ring approximation for computing gradients of Variational Quantum Eigensolver for Combinatorial Optimization
Variational Quantum algorithms, especially Quantum Approximate Optimizat...
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06/18/2023
On the Global Convergence of Natural Actor-Critic with Two-layer Neural Network Parametrization
Actor-critic algorithms have shown remarkable success in solving state-o...
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05/30/2023
FERN: Leveraging Graph Attention Networks for Failure Evaluation and Robust Network Design
Robust network design, which aims to guarantee network availability unde...
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05/27/2023
Hierarchical Deep Counterfactual Regret Minimization
Imperfect Information Games (IIGs) offer robust models for scenarios whe...
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05/26/2023
A Unified Approach for Maximizing Continuous DR-submodular Functions
This paper presents a unified approach for maximizing continuous DR-subm...
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05/22/2023
Multi-task Hierarchical Adversarial Inverse Reinforcement Learning
Multi-task Imitation Learning (MIL) aims to train a policy capable of pe...
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05/04/2023
Reinforcement Learning with Delayed, Composite, and Partially Anonymous Reward
We investigate an infinite-horizon average reward Markov Decision Proces...
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03/23/2023
Stochastic Submodular Bandits with Delayed Composite Anonymous Bandit Feedback
This paper investigates the problem of combinatorial multiarmed bandits ...
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03/15/2023
Towards Cooperative Federated Learning over Heterogeneous Edge/Fog Networks
Federated learning (FL) has been promoted as a popular technique for tra...
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02/16/2023
Quantum Computing Provides Exponential Regret Improvement in Episodic Reinforcement Learning
In this paper, we investigate the problem of episodic reinforcement lear...
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02/13/2023
FilFL: Accelerating Federated Learning via Client Filtering
Federated learning is an emerging machine learning paradigm that enables...
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02/02/2023
Randomized Greedy Learning for Non-monotone Stochastic Submodular Maximization Under Full-bandit Feedback
We investigate the problem of unconstrained combinatorial multi-armed ba...
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01/30/2023
A Framework for Adapting Offline Algorithms to Solve Combinatorial Multi-Armed Bandit Problems with Bandit Feedback
We investigate the problem of stochastic, combinatorial multi-armed band...
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01/23/2023
Quantum Heavy-tailed Bandits
In this paper, we study multi-armed bandits (MAB) and stochastic linear ...
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01/13/2023
Mean-Field Control based Approximation of Multi-Agent Reinforcement Learning in Presence of a Non-decomposable Shared Global State
Mean Field Control (MFC) is a powerful approximation tool to solve large...
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12/01/2022
ODPP: A Unified Algorithm Framework for Unsupervised Option Discovery based on Determinantal Point Process
Learning rich skills through temporal abstractions without supervision o...
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11/22/2022
Online Federated Learning via Non-Stationary Detection and Adaptation amidst Concept Drift
Federated Learning (FL) is an emerging domain in the broader context of ...
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11/14/2022
On the Global Convergence of Fitted Q-Iteration with Two-layer Neural Network Parametrization
Deep Q-learning based algorithms have been applied successfully in many ...
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10/07/2022
Multi-agent Deep Covering Option Discovery
The use of options can greatly accelerate exploration in reinforcement l...
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10/05/2022
Hierarchical Adversarial Inverse Reinforcement Learning
Hierarchical Imitation Learning (HIL) has been proposed to recover highl...
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09/15/2022
Mean-Field Approximation of Cooperative Constrained Multi-Agent Reinforcement Learning (CMARL)
Mean-Field Control (MFC) has recently been proven to be a scalable tool ...
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09/07/2022
On the Near-Optimality of Local Policies in Large Cooperative Multi-Agent Reinforcement Learning
We show that in a cooperative N-agent network, one can design locally ex...
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07/18/2022
A Community-Aware Framework for Social Influence Maximization
We consider the Influence Maximization (IM) problem: 'if we can try to c...
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06/22/2022
PAC: Assisted Value Factorisation with Counterfactual Predictions in Multi-Agent Reinforcement Learning
Multi-agent reinforcement learning (MARL) has witnessed significant prog...
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06/17/2022
FedNew: A Communication-Efficient and Privacy-Preserving Newton-Type Method for Federated Learning
Newton-type methods are popular in federated learning due to their fast ...
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06/12/2022
Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Conservative Natural Policy Gradient Primal-Dual Algorithm
We consider the problem of constrained Markov decision process (CMDP) in...
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03/26/2022
Multi-Edge Server-Assisted Dynamic Federated Learning with an Optimized Floating Aggregation Point
We propose cooperative edge-assisted dynamic federated learning (CE-FL)....
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02/28/2022
Can Mean Field Control (MFC) Approximate Cooperative Multi Agent Reinforcement Learning (MARL) with Non-Uniform Interaction?
Mean-Field Control (MFC) is a powerful tool to solve Multi-Agent Reinfor...
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02/13/2022
Deep Learning based Coverage and Rate Manifold Estimation in Cellular Networks
This article proposes Convolutional Neural Network-based Auto Encoder (C...
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02/07/2022
Parallel Successive Learning for Dynamic Distributed Model Training over Heterogeneous Wireless Networks
Federated learning (FedL) has emerged as a popular technique for distrib...
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01/25/2022
Coded Caching with Heterogeneous User Profiles
Coded caching utilizes pre-fetching during off-peak hours and multi-cast...
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01/21/2022
Tensor Ring Parametrized Variational Quantum Circuits for Large Scale Quantum Machine Learning
Quantum Machine Learning (QML) is an emerging research area advocating t...
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01/20/2022
Multi-agent Covering Option Discovery based on Kronecker Product of Factor Graphs
Covering option discovery has been developed to improve the exploration ...
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01/04/2022
Value Functions Factorization with Latent State Information Sharing in Decentralized Multi-Agent Policy Gradients
Value function factorization via centralized training and decentralized ...
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10/29/2021
Learning Circular Hidden Quantum Markov Models: A Tensor Network Approach
In this paper, we propose circular Hidden Quantum Markov Models (c-HQMMs...
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10/22/2021
Convergence Rates of Average-Reward Multi-agent Reinforcement Learning via Randomized Linear Programming
In tabular multi-agent reinforcement learning with average-cost criterio...
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09/13/2021
Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Primal-Dual Approach
Reinforcement learning is widely used in applications where one needs to...
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09/12/2021
Concave Utility Reinforcement Learning with Zero-Constraint Violations
We consider the problem of tabular infinite horizon concave utility rein...
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09/09/2021
DROP: Deep relocating option policy for optimal ride-hailing vehicle repositioning
In a ride-hailing system, an optimal relocation of vacant vehicles can s...
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09/09/2021
On the Approximation of Cooperative Heterogeneous Multi-Agent Reinforcement Learning (MARL) using Mean Field Control (MFC)
Mean field control (MFC) is an effective way to mitigate the curse of di...
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08/30/2021
An FEA surrogate model with Boundary Oriented Graph Embedding approach
In this work, we present a Boundary Oriented Graph Embedding (BOGE) appr...
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06/12/2021
Markov Decision Processes with Long-Term Average Constraints
We consider the problem of constrained Markov Decision Process (CMDP) wh...
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05/31/2021
Energy-Efficient and Federated Meta-Learning via Projected Stochastic Gradient Ascent
In this paper, we propose an energy-efficient federated meta-learning fr...
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05/28/2021
Joint Optimization of Multi-Objective Reinforcement Learning with Policy Gradient Based Algorithm
Many engineering problems have multiple objectives, and the overall aim ...
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04/24/2021
Quantum Causal Inference in the Presence of Hidden Common Causes: an Entropic Approach
Quantum causality is an emerging field of study which has the potential ...
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04/01/2021
AdaPool: A Diurnal-Adaptive Fleet Management Framework using Model-Free Deep Reinforcement Learning and Change Point Detection
This paper introduces an adaptive model-free deep reinforcement approach...
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03/05/2021
