b'Cong Shen'

research

∙ 06/23/2023

Torsion Graph Neural Networks

Geometric deep learning (GDL) models have demonstrated a great potential...

0 Cong Shen, et al. ∙

research

∙ 06/23/2023

Curvature-enhanced Graph Convolutional Network for Biomolecular Interaction Prediction

Geometric deep learning has demonstrated a great potential in non-Euclid...

0 Cong Shen, et al. ∙

research

∙ 06/22/2023

Molecular geometric deep learning

Geometric deep learning (GDL) has demonstrated huge power and enormous p...

0 Cong Shen, et al. ∙

research

∙ 06/14/2023

Provably Efficient Offline Reinforcement Learning with Perturbed Data Sources

Existing theoretical studies on offline reinforcement learning (RL) most...

0 Chengshuai Shi, et al. ∙

research

∙ 06/14/2023

Differentially Private Wireless Federated Learning Using Orthogonal Sequences

We propose a novel privacy-preserving uplink over-the-air computation (A...

0 Xizixiang Wei, et al. ∙

research

∙ 06/09/2023

Near-optimal Conservative Exploration in Reinforcement Learning under Episode-wise Constraints

This paper investigates conservative exploration in reinforcement learni...

0 Donghao Li, et al. ∙

research

∙ 05/06/2023

On High-dimensional and Low-rank Tensor Bandits

Most existing studies on linear bandits focus on the one-dimensional cha...

0 Chengshuai Shi, et al. ∙

research

∙ 05/03/2023

Reward Teaching for Federated Multi-armed Bandits

Most of the existing federated multi-armed bandits (FMAB) designs are ba...

0 Chengshuai Shi, et al. ∙

research

∙ 04/21/2023

Joint Client Assignment and UAV Route Planning for Indirect-Communication Federated Learning

Federated Learning (FL) is a machine learning approach that enables the ...

0 Jieming Bian, et al. ∙

research

∙ 02/14/2023

Federated Learning via Indirect Server-Client Communications

Federated Learning (FL) is a communication-efficient and privacy-preserv...

0 Jieming Bian, et al. ∙

research

∙ 02/11/2023

Communication and Storage Efficient Federated Split Learning

Federated learning (FL) is a popular distributed machine learning (ML) p...

0 Yujia Mu, et al. ∙

research

∙ 02/04/2023

Cross-Layer Federated Learning Optimization in MIMO Networks

In this paper, the performance optimization of federated learning (FL), ...

0 Sihua Wang, et al. ∙

research

∙ 04/11/2022

On Top-k Selection from m-wise Partial Rankings via Borda Counting

We analyze the performance of the Borda counting algorithm in a non-para...

2 Wenjing Chen, et al. ∙

research

∙ 02/12/2022

On Federated Learning with Energy Harvesting Clients

Catering to the proliferation of Internet of Things devices and distribu...

7 Cong Shen, et al. ∙

research

∙ 01/29/2022

Random Orthogonalization for Federated Learning in Massive MIMO Systems

We propose a novel uplink communication method, coined random orthogonal...

0 Xizixiang Wei, et al. ∙

research

∙ 12/20/2021

Learning for Robust Combinatorial Optimization: Algorithm and Application

Learning to optimize (L2O) has recently emerged as a promising approach ...

18 Zhihui Shao, et al. ∙

research

∙ 10/27/2021

(Almost) Free Incentivized Exploration from Decentralized Learning Agents

Incentivized exploration in multi-armed bandits (MAB) has witnessed incr...

5 Chengshuai Shi, et al. ∙

research

∙ 10/27/2021

Heterogeneous Multi-player Multi-armed Bandits: Closing the Gap and Generalization

Despite the significant interests and many progresses in decentralized m...

5 Chengshuai Shi, et al. ∙

research

∙ 10/27/2021

Federated Linear Contextual Bandits

This paper presents a novel federated linear contextual bandits model, w...

7 Ruiquan Huang, et al. ∙

research

∙ 06/25/2021

Multi-player Multi-armed Bandits with Collision-Dependent Reward Distributions

We study a new stochastic multi-player multi-armed bandits (MP-MAB) prob...

2 Chengshuai Shi, et al. ∙

research

∙ 04/14/2021

Resource Rationing for Wireless Federated Learning: Concept, Benefits, and Challenges

We advocate a new resource allocation framework, which we term resource ...

5 Cong Shen, et al. ∙

research

∙ 02/25/2021

Federated Multi-armed Bandits with Personalization

A general framework of personalized federated multi-armed bandits (PF-MA...

12 Chengshuai Shi, et al. ∙

research

∙ 01/28/2021

Federated Multi-Armed Bandits

Federated multi-armed bandits (FMAB) is a new bandit paradigm that paral...

13 Chengshuai Shi, et al. ∙

research

∙ 01/26/2021

SDF-Bayes: Cautious Optimism in Safe Dose-Finding Clinical Trials with Drug Combinations and Heterogeneous Patient Groups

Phase I clinical trials are designed to test the safety (non-toxicity) o...

6 Hyun-Suk Lee, et al. ∙

research

∙ 01/06/2021

Federated Learning over Noisy Channels: Convergence Analysis and Design Examples

Does Federated Learning (FL) work when both uplink and downlink communic...

13 Xizixiang Wei, et al. ∙

research

∙ 12/11/2020

Underactuated Motion Planning and Control for Jumping with Wheeled-Bipedal Robots

This paper studies jumping for wheeled-bipedal robots, a motion that tak...

0 Hua Chen, et al. ∙

research

∙ 12/07/2020

Design and Analysis of Uplink and Downlink Communications for Federated Learning

Communication has been known to be one of the primary bottlenecks of fed...

5 Sihui Zheng, et al. ∙

research

∙ 11/02/2020

On No-Sensing Adversarial Multi-player Multi-armed Bandits with Collision Communications

We study the notoriously difficult no-sensing adversarial multi-player m...

5 Chengshuai Shi, et al. ∙

research

∙ 08/20/2020

Autonomous Social Distancing in Urban Environments using a Quadruped Robot

COVID-19 pandemic has become a global challenge faced by people all over...

0 Tingxiang Fan, et al. ∙

research

∙ 06/14/2020

Robust Recursive Partitioning for Heterogeneous Treatment Effects with Uncertainty Quantification

Subgroup analysis of treatment effects plays an important role in applic...

0 Hyun-Suk Lee, et al. ∙

research

∙ 06/09/2020

Learning for Dose Allocation in Adaptive Clinical Trials with Safety Constraints

Phase I dose-finding trials are increasingly challenging as the relation...

0 Cong Shen, et al. ∙

research

∙ 03/05/2020

Stochastic Linear Contextual Bandits with Diverse Contexts

In this paper, we investigate the impact of context diversity on stochas...

0 Weiqiang Wu, et al. ∙

research

∙ 02/29/2020

Decentralized Multi-player Multi-armed Bandits with No Collision Information

The decentralized stochastic multi-player multi-armed bandit (MP-MAB) pr...

0 Chengshuai Shi, et al. ∙

research

∙ 01/12/2020

Collaborative Multi-Agent Multi-Armed Bandit Learning for Small-Cell Caching

This paper investigates learning-based caching in small-cell networks (S...

0 Xianzhe Xu, et al. ∙

research

∙ 01/08/2020

Contextual Constrained Learning for Dose-Finding Clinical Trials

Clinical trials in the medical domain are constrained by budgets. The nu...

0 Hyun-Suk Lee, et al. ∙

research

∙ 06/10/2019

A Regression Approach to Certain Information Transmission Problems

A general information transmission model, under independent and identica...

0 Wenyi Zhang, et al. ∙

research

∙ 01/23/2019

Online Learning with Diverse User Preferences

In this paper, we investigate the impact of diverse user preference on l...

0 Chao Gan, et al. ∙

research

∙ 07/26/2018

Towards Optimal Power Control via Ensembling Deep Neural Networks

A deep neural network (DNN) based power control method is proposed, whic...

0 Fei Liang, et al. ∙

research

∙ 05/22/2018

Cost-aware Cascading Bandits

In this paper, we propose a cost-aware cascading bandits model, a new va...

0 Ruida Zhou, et al. ∙

research

∙ 04/11/2018

Cost-Aware Learning and Optimization for Opportunistic Spectrum Access

In this paper, we investigate cost-aware joint learning and optimization...

0 Chao Gan, et al. ∙

research

∙ 02/22/2018

Regional Multi-Armed Bandits

We consider a variant of the classic multi-armed bandit problem where th...

0 Zhiyang Wang, et al. ∙

research

∙ 01/11/2018

New Results on Multilevel Diversity Coding with Secure Regeneration

The problem of multilevel diversity coding with secure regeneration is r...

0 Shuo Shao, et al. ∙

research

∙ 12/09/2017

Multilevel Diversity Coding with Secure Regeneration: Separate Coding Achieves the MBR Point

The problem of multilevel diversity coding with secure regeneration (MDC...

0 Shuo Shao, et al. ∙

research

∙ 07/18/2017

An Iterative BP-CNN Architecture for Channel Decoding

Inspired by recent advances in deep learning, we propose a novel iterati...

0 Fei Liang, et al. ∙

Cong Shen

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