Optimal Resource Allocation in Wireless Multiaccess Video Transmissions. - Cong Shen 001; Mihaela van der Schaar (ICC, 2007)

Generalized Soft-Output Layered Orthogonal Lattice Detector for Golden Code. - Cong Shen 001; Michael P. Fitz; Massimiliano Siti (WCNC, 2007)

Hybrid ARQ schemes in multiple-antenna slow fading channels: A capacity perspective. - Cong Shen 001; Michael P. Fitz (ACSCC, 2008)

On the Design of Modern Multilevel Coded Modulation for Unequal Error Protection. - Cong Shen 001; Michael P. Fitz (ICC, 2008)

Aggressive Transmission with ARQ in Quasi-Static Fading Channels. - Cong Shen 001; Tie Liu 002; Michael P. Fitz (ICC, 2008)

A utility maximization approach to the design of unequal error protection with multilevel codes. - Cong Shen 001; Michael P. Fitz (ISIT, 2008)

MIMO-OFDM Beamforming for Improved Channel Estimation. - Cong Shen 001; Michael P. Fitz (IEEE J. Sel. Areas Commun., 2008)

Optimal Resource Allocation for Multimedia Applications over Multiaccess Fading Channels. - Cong Shen 001; Mihaela van der Schaar (IEEE Trans. Wirel. Commun., 2008)

Dynamic spatial spectrum access with opportunistic orthogonalization. - Cong Shen 001; Michael P. Fitz (CISS, 2009)

On the average rate performance of hybrid-ARQ in quasi-static fading channels. - Cong Shen 001; Tie Liu 002; Michael P. Fitz (IEEE Trans. Commun., 2009)

Opportunistic Spatial Orthogonalization and Its Application in Fading Cognitive Radio Networks. - Cong Shen 001; Michael P. Fitz (IEEE J. Sel. Top. Signal Process., 2011)

Hybrid ARQ in Multiple-Antenna Slow Fading Channels: Performance Limits and Optimal Linear Dispersion Code Design. - Cong Shen 001; Michael P. Fitz (IEEE Trans. Inf. Theory, 2011)

Silence is gold: Strategic small cell interference management using tokens. - Cong Shen 001; Jie Xu 001; Mihaela van der Schaar (GLOBECOM, 2014)

An uplink interference analysis for massive MIMO systems with MRC and ZF receivers. - Ning Liang; Wenyi Zhang 001; Cong Shen 001 (WCNC, 2015)

Silence is Gold: Strategic Interference Mitigation Using Tokens in Heterogeneous Small Cell Networks. - Cong Shen 001; Jie Xu 001; Mihaela van der Schaar (IEEE J. Sel. Areas Commun., 2015)

DARC: Timely Classification with Randomly Delayed Features. - Jie Xu 001; Qi Cai; Cong Shen 001 (GLOBECOM, 2016)

Less is More: Participation Incentives in D2D-enhanced Mobile Edge Computing under Infectious DDoS Attacks. - Jie Xu 001; Lixing Chen; Kun Liu; Cong Shen 001 (CoRR, 2016)

A Non-Stochastic Learning Approach to Energy Efficient Mobility Management. - Cong Shen 001; Cem Tekin; Mihaela van der Schaar (IEEE J. Sel. Areas Commun., 2016)

On the effective capacities of distributed and co-located large-scale antenna systems. - Cong Shen 001; Zehao Yu; Chang Wen Chen; Feng Wu 001 (ICC, 2017)

Learn to adapt: Self-optimizing small cell transmit power with correlated bandit learning. - Zhiyang Wang; Cong Shen 001; Xiliang Luo; Mihaela van der Schaar (ICC, 2017)

DL CSI acquisition and feedback in FDD massive MIMO via path aligning. - Xiliang Luo; Xiaoyu Zhang 005; Penghao Cai; Cong Shen 001; Die Hu 002; Hua Qian (ICUFN, 2017)

On scheduling policies in the presence of heavy-tailed interference. - Hang Wu; Cong Shen 001; Shengbo Chen (ITA, 2017)

Aligning DL paths for scalable CSI feedback in FDD massive MIMO. - Xiliang Luo; Penghao Cai; Xiaoyu Zhang 005; Cong Shen 001; Hua Qian (IWCMC, 2017)

A Cyber-Physical Design for Indoor Temperature Monitoring Using Wireless Sensor Networks. - Cong Shen 001; Shengbo Chen (WCNC, 2017)

A Learning Approach to Frequent Handover Mitigations in 3GPP Mobility Protocols. - Cong Shen 001; Mihaela van der Schaar (WCNC, 2017)

Online Geographical Load Balancing for Energy-Harvesting Mobile Edge Computing. - Jie Xu 001; Hang Wu; Lixing Chen; Cong Shen 001 (CoRR, 2017)

On Energy Efficient Uplink Multi-User MIMO with Shared LNA Control. - Zehao Yu; Cong Shen 001; Pengkai Zhao; Xiliang Luo (CoRR, 2017)

Small Cell Transmit Power Assignment Based on Correlated Bandit Learning. - Zhiyang Wang; Cong Shen 001 (IEEE J. Sel. Areas Commun., 2017)

On the Tradeoff Region of Secure Exact-Repair Regenerating Codes. - Shuo Shao 001; Tie Liu 002; Chao Tian 002; Cong Shen 001 (IEEE Trans. Inf. Theory, 2017)

A Scalable Framework for CSI Feedback in FDD Massive MIMO via DL Path Aligning. - Xiliang Luo; Penghao Cai; Xiaoyu Zhang 005; Die Hu 002; Cong Shen 001 (IEEE Trans. Signal Process., 2017)

Regional Multi-Armed Bandits. - Zhiyang Wang; Ruida Zhou; Cong Shen 001 (AISTATS, 2018)

Opportunistic Spectrum Access via Good Arm Identification. - Zhiyang Wang; Ziyu Ying 002; Cong Shen 001 (GlobalSIP, 2018)

Sparse Spectrum Reuse in HetNets with Relays. - Shengda Jin; Zhaowei Zhu; Cong Shen 001; Sadiq Ali; Hua Qian; Xiliang Luo (GLOBECOM, 2018)

How to Interconnect for Massive Mimo Self-Calibration? - Fuqian Yang; Hanyu Zhu; Cong Shen 001; Linglong Dai; Xiliang Luo (ICASSP, 2018)

Exploiting Noise Correlation for Channel Decoding with Convolutional Neural Networks. - Fei Liang; Cong Shen 001; Feng Wu 001 (ICC, 2018)

Small Cell Power Assignment with Unimodal Continuum-Armed Bandit Learning. - Zhiyang Wang; Cong Shen 001 (ICC Workshops, 2018)

Online Geographical Load Balancing for Energy-Harvesting Mobile Edge Computing. - Hang Wu; Lixing Chen; Cong Shen 001; Wujie Wen; Jie Xu 001 (ICC, 2018)

A Non-Stationary Online Learning Approach to Mobility Management. - Yiming Zhou; Cong Shen 001; Xiliang Luo; Mihaela van der Schaar (ICC, 2018)

Downlink Multi-User MIMO Precoding Design Via Signal-Over-Leakage Capacity. - Cong Shen 001 (IEEE Access, 2018)

New results on multilevel diversity coding with secure regeneration. - Shuo Shao 001; Tie Liu 002; Chao Tian 002; Cong Shen 001 (Sci. China Inf. Sci., 2018)

Multilevel Diversity Coding with Secure Regeneration: Separate Coding Achieves the MBR Point. - Shuo Shao 001; Tie Liu 002; Chao Tian 002; Cong Shen 001 (Entropy, 2018)

An Iterative BP-CNN Architecture for Channel Decoding. - Fei Liang; Cong Shen 001; Feng Wu 001 (IEEE J. Sel. Top. Signal Process., 2018)

Generalized Global Bandit and Its Application in Cellular Coverage Optimization. - Cong Shen 001; Ruida Zhou; Cem Tekin; Mihaela van der Schaar (IEEE J. Sel. Top. Signal Process., 2018)

Regional Multi-Armed Bandits With Partial Informativeness. - Zhiyang Wang; Ruida Zhou; Cong Shen 001 (IEEE Trans. Signal Process., 2018)

Designing Security-Aware Incentives for Computation Offloading via Device-to-Device Communication. - Jie Xu 001; Lixing Chen; Kun Liu; Cong Shen 001 (IEEE Trans. Wirel. Commun., 2018)

Privacy-Aware Edge Computing Based on Adaptive DNN Partitioning. - Chengshuai Shi; Lixing Chen; Cong Shen 001; Linqi Song; Jie Xu 001 (GLOBECOM, 2019)

Power Control for Interference Management via Ensembling Deep Neural Networks. - Fei Liang; Cong Shen 001; Wei Yu 001; Feng Wu 001 (ICCC, 2019)

Online Learning with Diverse User Preferences. - Chao Gan; Jing Yang 002; Ruida Zhou; Cong Shen 001 (ISIT, 2019)

A Cascading Bandit Approach To Efficient Mobility Management In Ultra-Dense Networks. - Chao Wang 073; Ruida Zhou; Jing Yang 002; Cong Shen 001 (MLSP, 2019)

A Regression Approach to Certain Information Transmission Problems. - Wenyi Zhang 001; Yizhu Wang; Cong Shen 001; Ning Liang (IEEE J. Sel. Areas Commun., 2019)

Cost-Aware Learning and Optimization for Opportunistic Spectrum Access. - Chao Gan; Ruida Zhou; Jing Yang 002; Cong Shen 001 (IEEE Trans. Cogn. Commun. Netw., 2019)

Universal Best Arm Identification. - Cong Shen 001 (IEEE Trans. Signal Process., 2019)

A Non-Stationary Online Learning Approach to Mobility Management. - Yiming Zhou; Cong Shen 001; Mihaela van der Schaar (IEEE Trans. Wirel. Commun., 2019)

Thresholded Wirtinger Flow for Fast Millimeter Wave Beam Alignment. - Chao Gan; Jing Yang 002; Cong Shen 001 (ACSSC, 2020)

MIMO Receive Antenna Selection via Deep Learning and Greedy Adaptation. - Cong Shen 001; Donghao Li; Jing Yang 002 (ACSSC, 2020)

Contextual Constrained Learning for Dose-Finding Clinical Trials. - Hyun-Suk Lee; Cong Shen 001; James Jordon; Mihaela van der Schaar (AISTATS, 2020)

Decentralized Multi-player Multi-armed Bandits with No Collision Information. - Chengshuai Shi; Wei Xiong 015; Cong Shen 001; Jing Yang 002 (AISTATS, 2020)

Stochastic Linear Contextual Bandits with Diverse Contexts. - Weiqiang Wu; Jing Yang 002; Cong Shen 001 (AISTATS, 2020)

Learning for Dose Allocation in Adaptive Clinical Trials with Safety Constraints. - Cong Shen 001; Zhiyang Wang; Sofia S. Villar; Mihaela van der Schaar (ICML, 2020)

Federated Learning with Heterogeneous Quantization. - Cong Shen 001; Shengbo Chen (SEC, 2020)

Deep Reinforcement Learning based Wireless Network Optimization: A Comparative Study. - Kun Yang 011; Cong Shen 001; Tie Liu 002 (INFOCOM Workshops, 2020)

Robust Recursive Partitioning for Heterogeneous Treatment Effects with Uncertainty Quantification. - Hyun-Suk Lee; Yao Zhang; William R. Zame; Cong Shen 001; Jang-Won Lee 001; Mihaela van der Schaar (NeurIPS, 2020)

On Scheduling Policies With Heavy-Tailed Dynamics in Wireless Queueing Systems. - Shengbo Chen; Lanxue Zhang; Cong Shen 001; Keping Yu; San Hlaing Myint; Zheng Wen 001 (IEEE Access, 2020)

Towards Optimal Power Control via Ensembling Deep Neural Networks. - Fei Liang; Cong Shen 001; Wei Yu 001; Feng Wu 001 (IEEE Trans. Commun., 2020)

Cost-Aware Cascading Bandits. - Chao Gan; Ruida Zhou; Jing Yang 002; Cong Shen 001 (IEEE Trans. Signal Process., 2020)

Collaborative Multi-Agent Multi-Armed Bandit Learning for Small-Cell Caching. - Xianzhe Xu; Meixia Tao; Cong Shen 001 (IEEE Trans. Wirel. Commun., 2020)

Improved Low-Resolution Quantized SIMO Estimation via Deep Learning. - Saichao Liu; Shengbo Chen; Cong Shen 001; Mohamed A. Ismail; Roshan Kumar (IEEE Wirel. Commun. Lett., 2020)

Federated Multi-Armed Bandits. - Chengshuai Shi; Cong Shen 001 (AAAI, 2021)

SDF-Bayes: Cautious Optimism in Safe Dose-Finding Clinical Trials with Drug Combinations and Heterogeneous Patient Groups. - Hyun-Suk Lee; Cong Shen 001; William R. Zame; Jang-Won Lee 001; Mihaela van der Schaar (AISTATS, 2021)

Federated Multi-armed Bandits with Personalization. - Chengshuai Shi; Cong Shen 001; Jing Yang 002 (AISTATS, 2021)

A Machine Learning Approach for Rate Prediction in Multicast File-stream Distribution Networks. - Yujia Mu; Yuanlong Tan; Malathi Veeraraghavan; Cong Shen 001 (GLOBECOM, 2021)

On Energy Efficient Uplink Multi-User MIMO with Shared LNA Control. - Cong Shen 001; Pengkai Zhao; Xiliang Luo (ICC, 2021)

Federated Learning over Noisy Channels. - Xizixiang Wei; Cong Shen 001 (ICC, 2021)

An Attackability Perspective on No-Sensing Adversarial Multi-player Multi-armed Bandits. - Chengshuai Shi; Cong Shen 001 (ISIT, 2021)

Federated Linear Contextual Bandits. - Ruiquan Huang; Weiqiang Wu; Jing Yang 002; Cong Shen 001 (NeurIPS, 2021)

Heterogeneous Multi-player Multi-armed Bandits: Closing the Gap and Generalization. - Chengshuai Shi; Wei Xiong 015; Cong Shen 001; Jing Yang 002 (NeurIPS, 2021)

(Almost) Free Incentivized Exploration from Decentralized Learning Agents. - Chengshuai Shi; Haifeng Xu; Wei Xiong 015; Cong Shen 001 (NeurIPS, 2021)

Resource Rationing for Wireless Federated Learning: Concept, Benefits, and Challenges. - Cong Shen 001; Jie Xu 001; Sihui Zheng; Xiang Chen 007 (IEEE Commun. Mag., 2021)

Design and Analysis of Uplink and Downlink Communications for Federated Learning. - Sihui Zheng; Cong Shen 001; Xiang Chen 007 (IEEE J. Sel. Areas Commun., 2021)

On No-Sensing Adversarial Multi-Player Multi-Armed Bandits With Collision Communications. - Chengshuai Shi; Cong Shen 001 (IEEE J. Sel. Areas Inf. Theory, 2021)

Collaborative Service Placement for Edge Computing in Dense Small Cell Networks. - Lixing Chen; Cong Shen 001; Pan Zhou 001; Jie Xu 001 (IEEE Trans. Mob. Comput., 2021)

Multi-Player Multi-Armed Bandits With Collision-Dependent Reward Distributions. - Chengshuai Shi; Cong Shen 001 (IEEE Trans. Signal Process., 2021)

Dynamic Aggregation for Heterogeneous Quantization in Federated Learning. - Shengbo Chen; Cong Shen 001; Lanxue Zhang; Yuanmin Tang (IEEE Trans. Wirel. Commun., 2021)

Multi-Agent Reinforcement Learning for Wireless User Scheduling: Performance, Scalablility, and Generalization. - Kun Yang 011; Donghao Li; Cong Shen 001; Jing Yang 002; Shu-Ping Yeh; Jerry Sydir (IEEECONF, 2022)

On the Convergence of Hybrid Federated Learning with Server-Clients Collaborative Training. - Kun Yang 011; Cong Shen 001 (CISS, 2022)

On Federated Learning with Energy Harvesting Clients. - Cong Shen 001; Jing Yang 002; Jie Xu 001 (ICASSP, 2022)

A Self-Play Posterior Sampling Algorithm for Zero-Sum Markov Games. - Wei Xiong 015; Han Zhong 001; Chengshuai Shi; Cong Shen 001; Tong Zhang 001 (ICML, 2022)

Learning for Robust Combinatorial Optimization: Algorithm and Application. - Zhihui Shao; Jianyi Yang 001; Cong Shen 001; Shaolei Ren (INFOCOM, 2022)

Cascading Bandits with Two-Level Feedback. - Duo Cheng; Ruiquan Huang; Cong Shen 001; Jing Yang 002 (ISIT, 2022)

Optimizing Federated Averaging over Fading Channels. - Yujia Mu; Cong Shen 001; Yonina C. Eldar (ISIT, 2022)

8th SIGKDD International Workshop on Mining and Learning from Time Series - Deep Forecasting: Models, Interpretability, and Applications. - Sanjay Purushotham; Jun Huan; Cong Shen 001; Dongjin Song; Yuyang Wang 001; Jan Gasthaus; Hilaf Hasson; Youngsuk Park; Sungyong Seo; Yuriy Nevmyvaka (KDD, 2022)

MARS: Assisting Human with Information Processing Tasks Using Machine Learning. - Cong Shen 001; Zhaozhi Qian; Alihan Hüyük; Mihaela van der Schaar (ACM Trans. Comput. Heal., 2022)

Federated Learning Over Noisy Channels: Convergence Analysis and Design Examples. - Xizixiang Wei; Cong Shen 001 (IEEE Trans. Cogn. Commun. Netw., 2022)

Joint Optimal Quantization and Aggregation of Federated Learning Scheme in VANETs. - Yifei Li; Yijia Guo; Mamoun Alazab; Shengbo Chen; Cong Shen 001; Keping Yu (IEEE Trans. Intell. Transp. Syst., 2022)

On Top-k Selection From m-Wise Partial Rankings via Borda Counting. - Wenjing Chen 001; Ruida Zhou; Chao Tian 002; Cong Shen 001 (IEEE Trans. Signal Process., 2022)

Tx-Rx Reciprocity Calibration for Hybrid Massive MIMO Systems. - Xizixiang Wei; Yi Jiang 002; Xin Wang 003; Cong Shen 001 (IEEE Wirel. Commun. Lett., 2022)

Offline Reinforcement Learning for Wireless Network Optimization with Mixture Datasets. - Kun Yang 011; Cong Shen 001; Jing Yang 002; Shu-Ping Yeh; Jerry Sydir (ACSSC, 2023)

Federated Learning via Indirect Server-Client Communications. - Jieming Bian; Cong Shen 001; Jie Xu 001 (CISS, 2023)

Teaching Reinforcement Learning Agents via Reinforcement Learning. - Kun Yang 011; Chengshuai Shi; Cong Shen 001 (CISS, 2023)

MIMO Beamforming and Signal Modulation Design for Federated Learning Optimization. - Nuocheng Yang; Sihua Wang; Mingzhe Chen; Cong Shen 001; Changchuan Yin; Christopher G. Brinton (GLOBECOM, 2023)

Communication and Storage Efficient Federated Split Learning. - Yujia Mu; Cong Shen 001 (ICC, 2023)

FLORAS: Differentially Private Wireless Federated Learning Using Orthogonal Sequences. - Xizixiang Wei; Tianhao Wang 001; Ruiquan Huang; Cong Shen 001; Jing Yang 002; H. Vincent Poor (ICC, 2023)

Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game. - Wei Xiong 015; Han Zhong 001; Chengshuai Shi; Cong Shen 001; Liwei Wang 001; Tong Zhang 001 (ICLR, 2023)

Near-optimal Conservative Exploration in Reinforcement Learning under Episode-wise Constraints. - Donghao Li; Ruiquan Huang; Cong Shen 001; Jing Yang 002 (ICML, 2023)

Provably Efficient Offline Reinforcement Learning with Perturbed Data Sources. - Chengshuai Shi; Wei Xiong 015; Cong Shen 001; Jing Yang 002 (ICML, 2023)

Exploiting Feature Heterogeneity for Improved Generalization in Federated Multi-task Learning. - Renpu Liu; Jing Yang 002; Cong Shen 001 (ISIT, 2023)

On High-dimensional and Low-rank Tensor Bandits. - Chengshuai Shi; Cong Shen 001; Nicholas D. Sidiropoulos (ISIT, 2023)

Reward Teaching for Federated Multi-armed Bandits. - Chengshuai Shi; Wei Xiong 015; Cong Shen 001; Jing Yang 002 (ISIT, 2023)

The 9th SIGKDD International Workshop on Mining and Learning from Time Series. - Sanjay Purushotham; Dongjin Song; Qingsong Wen; Jun Huan; Cong Shen 001; Yuriy Nevmyvaka (KDD, 2023)

Federated Linear Bandits with Finite Adversarial Actions. - Li Fan; Ruida Zhou; Chao Tian 002; Cong Shen 001 (NeurIPS, 2023)

Cross-Layer Federated Learning Optimization in MIMO Networks. - Sihua Wang; Mingzhe Chen; Cong Shen 001; Changchuan Yin; Christopher G. Brinton (CoRR, 2023)

Joint Client Assignment and UAV Route Planning for Indirect-Communication Federated Learning. - Jieming Bian; Cong Shen 001; Jie Xu 001 (CoRR, 2023)

Differentially Private Wireless Federated Learning Using Orthogonal Sequences. - Xizixiang Wei; Tianhao Wang 001; Ruiquan Huang; Cong Shen 001; Jing Yang 002; H. Vincent Poor (CoRR, 2023)

Reward Teaching for Federated Multiarmed Bandits. - Chengshuai Shi; Wei Xiong 015; Cong Shen 001; Jing Yang 002 (IEEE Trans. Signal Process., 2023)

On the Convergence of Hybrid Server-Clients Collaborative Training. - Kun Yang 011; Shengbo Chen; Cong Shen 001 (IEEE J. Sel. Areas Commun., 2023)

Performance Optimization for Noise Interference Privacy Protection in Federated Learning. - Zihao Peng; Boyuan Li; Le Li; Shengbo Chen; Guanghui Wang 003; Hong Rao; Cong Shen 001 (IEEE Trans. Cogn. Commun. Netw., 2023)

FastGAS: Fast Graph-based Annotation Selection for In-Context Learning. - Zihan Chen 002; Song Wang 013; Cong Shen 001; Jundong Li (ACL (Findings), 2024)

Average Reward Reinforcement Learning for Wireless Radio Resource Management. - Kun Yang 011; Jing Yang 002; Cong Shen 001 (IEEECONF, 2024)

Advancing RAN Slicing with Offline Reinforcement Learning. - Kun Yang 011; Shu-Ping Yeh; Menglei Zhang; Jerry Sydir; Jing Yang 002; Cong Shen 001 (DySPAN, 2024)

Personalized Federated Learning with Attention-Based Client Selection. - Zihan Chen 002; Jundong Li; Cong Shen 001 (ICASSP, 2024)

An Autoencoder-Based Constellation Design for AirComp in Wireless Federated Learning. - Yujia Mu; Xizixiang Wei; Cong Shen 001 (ICC, 2024)

Federated Representation Learning in the Under-Parameterized Regime. - Renpu Liu; Cong Shen 001; Jing Yang 002 (ICML, 2024)

Verification of Machine Unlearning is Fragile. - Binchi Zhang; Zihan Chen 002; Cong Shen 001; Jundong Li (ICML, 2024)

The 10th Mining and Learning from Time Series Workshop: From Classical Methods to LLMs. - Sanjay Purushotham; Dongjin Song; Qingsong Wen; Jun Huan; Cong Shen 001; Stefan Zohren; Yuriy Nevmyvaka (KDD, 2024)

NL2Code-Reasoning and Planning with LLMs for Code Development. - Ye Xing; Jun Huan; Wee Hyong Tok; Cong Shen 001; Johannes Gehrke; Katherine Lin; Arjun Guha; Omer Tripp; Murali Krishna Ramanathan (KDD, 2024)

Efficient Prompt Optimization Through the Lens of Best Arm Identification. - Chengshuai Shi; Kun Yang 011; Zihan Chen 002; Jundong Li; Jing Yang 002; Cong Shen 001 (NeurIPS, 2024)

Transformers as Game Players: Provable In-context Game-playing Capabilities of Pre-trained Models. - Chengshuai Shi; Kun Yang 011; Jing Yang 002; Cong Shen 001 (NeurIPS, 2024)

Mixture of Demonstrations for In-Context Learning. - Song Wang 013; Zihan Chen 002; Chengshuai Shi; Cong Shen 001; Jundong Li (NeurIPS, 2024)

A Prototype Preceding Vehicle Identification System Development and Field Evaluation. - Zeyu Mu; Guancheng Tu; Austin Shi; Kun Yang 011; Yixin Sun; Cong Shen 001; B. Brian Park (VEHITS, 2024)

Best Arm Identification for Prompt Learning under a Limited Budget. - Chengshuai Shi; Kun Yang 011; Jing Yang 002; Cong Shen 001 (CoRR, 2024)

Safety in Graph Machine Learning: Threats and Safeguards. - Song Wang 013; Yushun Dong; Binchi Zhang; Zihan Chen 002; Xingbo Fu; Yinhan He; Cong Shen 001; Chuxu Zhang; Nitesh V. Chawla; Jundong Li (CoRR, 2024)

Neighborhood and Global Perturbations Supported SAM in Federated Learning: From Local Tweaks To Global Awareness. - Boyuan Li; Zihao Peng; Yafei Li; Mingliang Xu 001; Shengbo Chen; Baofeng Ji; Cong Shen 001 (CoRR, 2024)

On the Training Convergence of Transformers for In-Context Classification. - Wei Shen; Ruida Zhou; Jing Yang 002; Cong Shen 001 (CoRR, 2024)

Channel-Wise Mixed-Precision Quantization for Large Language Models. - Zihan Chen 002; Bike Xie; Jundong Li; Cong Shen 001 (CoRR, 2024)

Decision Feedback In-Context Symbol Detection over Block-Fading Channels. - Li Fan; Jing Yang 002; Cong Shen 001 (CoRR, 2024)

Stereoscopic artificial compound eyes for spatiotemporal perception in three-dimensional space. - Byungjoon Bae; Doeon Lee; Minseong Park; Yujia Mu; Yongmin Baek; Inbo Sim; Cong Shen 001; Kyusang Lee (Sci. Robotics, 2024)

Harnessing the Power of Federated Learning in Federated Contextual Bandits. - Chengshuai Shi; Ruida Zhou; Kun Yang 011; Cong Shen 001 (Trans. Mach. Learn. Res., 2024)

Accelerating Hybrid Federated Learning Convergence Under Partial Participation. - Jieming Bian; Lei Wang 199; Kun Yang 011; Cong Shen 001; Jie Xu 001 (IEEE Trans. Signal Process., 2024)

Federated Learning With Heterogeneous Quantization Bit Allocation and Aggregation for Internet of Things. - Shengbo Chen; Le Li; Guanghui Wang 003; Meng Pang; Cong Shen 001 (IEEE Internet Things J., 2024)

Random Orthogonalization for Federated Learning in Massive MIMO Systems. - Xizixiang Wei; Cong Shen 001; Jing Yang 002; H. Vincent Poor (IEEE Trans. Wirel. Commun., 2024)

Digital Over-the-Air Federated Learning in Multi-Antenna Systems. - Sihua Wang; Mingzhe Chen; Cong Shen 001; Changchuan Yin; Christopher G. Brinton (IEEE Trans. Wirel. Commun., 2024)

Offline Reinforcement Learning for Wireless Network Optimization With Mixture Datasets. - Kun Yang 011; Chengshuai Shi; Cong Shen 001; Jing Yang 002; Shu-Ping Yeh; Jaroslaw J. Sydir (IEEE Trans. Wirel. Commun., 2024)

A Shared Low-Rank Adaptation Approach to Personalized RLHF. - Renpu Liu; Peng Wang 105; Donghao Li; Cong Shen 001; Jing Yang 002 (AISTATS, 2025)

Cost-Aware Optimal Pairwise Pure Exploration. - Di Wu; Chengshuai Shi; Ruida Zhou; Cong Shen 001 (AISTATS, 2025)

Data-adaptive Differentially Private Prompt Synthesis for In-Context Learning. - Fengyu Gao; Ruida Zhou; Tianhao Wang 001; Cong Shen 001; Jing Yang 002 (ICLR, 2025)

On the Learn-to-Optimize Capabilities of Transformers in In-Context Sparse Recovery. - Renpu Liu; Ruida Zhou; Cong Shen 001; Jing Yang 002 (ICLR, 2025)

Augmenting Online RL with Offline Data is All You Need: A Unified Hybrid RL Algorithm Design and Analysis. - Ruiquan Huang; Donghao Li; Chengshuai Shi; Cong Shen 001; Jing Yang 002 (UAI, 2025)

Federated Learning for Diffusion Models. - Zihao Peng; Xijun Wang 001; Shengbo Chen; Hong Rao; Cong Shen 001 (CoRR, 2025)

Transformer-based Wireless Symbol Detection Over Fading Channels. - Li Fan; Jing Yang 002; Cong Shen 001 (CoRR, 2025)

A Survey of Scaling in Large Language Model Reasoning. - Zihan Chen 002; Song Wang 013; Zhen Tan 001; Xingbo Fu; Zhen Lei 001; Peng Wang 105; Huan Liu 001; Cong Shen 001; Jundong Li (CoRR, 2025)

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs. - Zihan Chen 002; Xingbo Fu; Yushun Dong; Jundong Li; Cong Shen 001 (CoRR, 2025)

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning. - Zihan Chen 002; Song Wang 013; Zhen Tan 001; Jundong Li; Cong Shen 001 (CoRR, 2025)

Graph Prompting for Graph Learning Models: Recent Advances and Future Directions. - Xingbo Fu; Zehong Wang; Zihan Chen 002; Jiazheng Li 012; Yaochen Zhu; Zhen Lei 001; Cong Shen 001; Yanfang Ye 001; Chuxu Zhang; Jundong Li (CoRR, 2025)

Chain-of-Thought Enhanced Shallow Transformers for Wireless Symbol Detection. - Li Fan; Peng Wang 105; Jing Yang 002; Cong Shen 001 (CoRR, 2025)

Indirect-Communication Federated Learning via Mobile Transporters. - Jieming Bian; Cong Shen 001; Mingzhe Chen; Jie Xu 001 (IEEE Trans. Mob. Comput., 2025)

Federated Split Learning with Improved Communication and Storage Efficiency. - Yujia Mu; Cong Shen 001 (CoRR, 2025)