DOA Estimation Based on Sparse Signal Recovery Utilizing Weighted l1-Norm Penalty. - Xu Xu 003; Xiaohan Wei; Zhongfu Ye (IEEE Signal Process. Lett., 2012)

DOA Estimation Using a Greedy Block Coordinate Descent Algorithm. - Xiaohan Wei; Yabo Yuan; Qing Ling (IEEE Trans. Signal Process., 2012)

Power aware wireless file downloading: A constrained restless bandit approach. - Xiaohan Wei; Michael J. Neely (WiOpt, 2014)

Recoverability of Group Sparse Signals from Corrupted Measurements via Robust Group Lasso. - Xiaohan Wei; Qing Ling; Zhu Han 001 (CoRR, 2015)

Robust group LASSO over decentralized networks. - Manxi Wang; Yongcheng Li; Xiaohan Wei; Qing Ling (GlobalSIP, 2016)

Delay optimal power aware opportunistic scheduling with mutual information accumulation. - Xiaohan Wei; Michael J. Neely (WiOpt, 2016)

Power-Aware Wireless File Downloading: A Lyapunov Indexing Approach to a Constrained Restless Bandit Problem. - Xiaohan Wei; Michael J. Neely (IEEE/ACM Trans. Netw., 2016)

Estimation of the covariance structure of heavy-tailed distributions. - Xiaohan Wei; Stanislav Minsker (NIPS, 2017)

Online Convex Optimization with Stochastic Constraints. - Hao Yu 002; Michael J. Neely; Xiaohan Wei (NIPS, 2017)

Data Center Server Provision: Distributed Asynchronous Control for Coupled Renewal Systems. - Xiaohan Wei; Michael J. Neely (IEEE/ACM Trans. Netw., 2017)

Solving Non-smooth Constrained Programs with Lower Complexity than mathcal{O}(1/ varepsilon): A Primal-Dual Homotopy Smoothing Approach. - Xiaohan Wei; Hao Yu 002; Qing Ling; Michael J. Neely (NeurIPS, 2018)

Solving Non-smooth Constrained Programs with Lower Complexity than 𝒪(1/ε): A Primal-Dual Homotopy Smoothing Approach. - Xiaohan Wei; Hao Yu 002; Qing Ling; Michael J. Neely (CoRR, 2018)

Online Learning in Weakly Coupled Markov Decision Processes: A Convergence Time Study. - Xiaohan Wei; Hao Yu 002; Michael J. Neely (Proc. ACM Meas. Anal. Comput. Syst., 2018)

Structured Signal Recovery From Non-Linear and Heavy-Tailed Measurements. - Larry Goldstein; Stanislav Minsker; Xiaohan Wei (IEEE Trans. Inf. Theory, 2018)

Distributed robust statistical learning: Byzantine mirror descent. - Dongsheng Ding; Xiaohan Wei; Mihailo R. Jovanovic (CDC, 2019)

On the statistical rate of nonlinear recovery in generative models with heavy-tailed data. - Xiaohan Wei; Zhuoran Yang; Zhaoran Wang 001 (ICML, 2019)

Fast Multi-Agent Temporal-Difference Learning via Homotopy Stochastic Primal-Dual Optimization. - Dongsheng Ding; Xiaohan Wei; Zhuoran Yang; Zhaoran Wang 001; Mihailo R. Jovanovic (CoRR, 2019)

Robust One-Bit Recovery via ReLU Generative Networks: Improved Statistical Rates and Global Landscape Analysis. - Shuang Qiu; Xiaohan Wei; Zhuoran Yang (CoRR, 2019)

The empirical optimal envelope and its application to local mean decomposition. - Linshan Jia; Qing Zhang; Xiang Zheng; Pulin Yao; Xiaogao He; Xiaohan Wei (Digit. Signal Process., 2019)

Robust One-Bit Recovery via ReLU Generative Networks: Near-Optimal Statistical Rate and Global Landscape Analysis. - Shuang Qiu; Xiaohan Wei; Zhuoran Yang (ICML, 2020)

Upper Confidence Primal-Dual Reinforcement Learning for CMDP with Adversarial Loss. - Shuang Qiu; Xiaohan Wei; Zhuoran Yang; Jieping Ye; Zhaoran Wang 001 (NeurIPS, 2020)

Upper Confidence Primal-Dual Optimization: Stochastically Constrained Markov Decision Processes with Adversarial Losses and Unknown Transitions. - Shuang Qiu; Xiaohan Wei; Zhuoran Yang; Jieping Ye; Zhaoran Wang 001 (CoRR, 2020)

Beyond 𝒪(#8730;T) Regret for Constrained Online Optimization: Gradual Variations and Mirror Prox. - Shuang Qiu; Xiaohan Wei (CoRR, 2020)

Single-Timescale Stochastic Nonconvex-Concave Optimization for Smooth Nonlinear TD Learning. - Shuang Qiu; Zhuoran Yang; Xiaohan Wei; Jieping Ye; Zhaoran Wang 001 (CoRR, 2020)

Fast Distributed Training of Deep Neural Networks: Dynamic Communication Thresholding for Model and Data Parallelism. - Vipul Gupta; Dhruv Choudhary; Ping Tak Peter Tang; Xiaohan Wei; Xing Wang; Yuzhen Huang; Arun Kejariwal; Kannan Ramchandran; Michael W. Mahoney (CoRR, 2020)

Online Primal-Dual Mirror Descent under Stochastic Constraints. - Xiaohan Wei; Hao Yu 002; Michael J. Neely (Proc. ACM Meas. Anal. Comput. Syst., 2020)

Provably Efficient Safe Exploration via Primal-Dual Policy Optimization. - Dongsheng Ding; Xiaohan Wei; Zhuoran Yang; Zhaoran Wang 001; Mihailo R. Jovanovic (AISTATS, 2021)

Byzantine-resilient distributed learning under constraints. - Dongsheng Ding; Xiaohan Wei; Hao Yu 002; Mihailo R. Jovanovic (ACC, 2021)

Provably Efficient Fictitious Play Policy Optimization for Zero-Sum Markov Games with Structured Transitions. - Shuang Qiu; Xiaohan Wei; Jieping Ye; Zhaoran Wang 001; Zhuoran Yang (ICML, 2021)

Training Recommender Systems at Scale: Communication-Efficient Model and Data Parallelism. - Vipul Gupta; Dhruv Choudhary; Ping Tak Peter Tang; Xiaohan Wei; Xing Wang; Yuzhen Huang; Arun Kejariwal; Kannan Ramchandran; Michael W. Mahoney (KDD, 2021)

Hierarchical Training: Scaling Deep Recommendation Models on Large CPU Clusters. - Yuzhen Huang; Xiaohan Wei; Xing Wang; Jiyan Yang; Bor-Yiing Su; Shivam Bharuka; Dhruv Choudhary; Zewei Jiang; Hai Zheng; Jack Langman (KDD, 2021)

Low-Precision Hardware Architectures Meet Recommendation Model Inference at Scale. - Zhaoxia Deng; Jongsoo Park; Ping Tak Peter Tang; Haixin Liu; Jie Yang; Hector Yuen; Jianyu Huang; Daya Shanker Khudia; Xiaohan Wei; Ellie Wen; Dhruv Choudhary; Raghuraman Krishnamoorthi; et al. (IEEE Micro, 2021)

Frequency-aware SGD for Efficient Embedding Learning with Provable Benefits. - Yan Li 074; Dhruv Choudhary; Xiaohan Wei; Baichuan Yuan; Bhargav Bhushanam; Tuo Zhao; Guanghui Lan (ICLR, 2022)

DHEN: A Deep and Hierarchical Ensemble Network for Large-Scale Click-Through Rate Prediction. - Buyun Zhang; Liang Luo; Xi Liu; Jay Li; Zeliang Chen; Weilin Zhang; Xiaohan Wei; Yuchen Hao; Michael Tsang; Wenjun Wang; Yang Liu; Huayu Li; et al. (CoRR, 2022)

Bayesian Network Structure Learning Method Based on Causal Direction Graph for Protein Signaling Networks. - Xiaohan Wei; Yulai Zhang; Cheng Wang (Entropy, 2022)

Gradient-Variation Bound for Online Convex Optimization with Constraints. - Shuang Qiu; Xiaohan Wei; Mladen Kolar (AAAI, 2023)

Provably Efficient Generalized Lagrangian Policy Optimization for Safe Multi-Agent Reinforcement Learning. - Dongsheng Ding; Xiaohan Wei; Zhuoran Yang; Zhaoran Wang 001; Mihailo R. Jovanovic (L4DC, 2023)

AdaEmbed: Adaptive Embedding for Large-Scale Recommendation Models. - Fan Lai 001; Wei Zhang; Rui Liu; William Tsai; Xiaohan Wei; Yuxi Hu 001; Sabin Devkota; Jianyu Huang; Jongsoo Park; Xing Liu; Zeliang Chen; Ellie Wen; et al. (OSDI, 2023)

Fine-Grained Embedding Dimension Optimization During Training for Recommender Systems. - Qinyi Luo; Penghan Wang; Wei Zhang; Fan Lai 001; Jiachen Mao; Xiaohan Wei; Jun Song; Wei-Yu Tsai; Shuai Yang; Yuxi Hu 001; Xuehai Qian (CoRR, 2024)

Convolutional Neural Network with Attention Mechanism and Visual Vibration Signal Analysis for Bearing Fault Diagnosis. - Qing Zhang; Xiaohan Wei; Ye Wang; Chenggang Hou (Sensors, 2024)

External Large Foundation Model: How to Efficiently Serve Trillions of Parameters for Online Ads Recommendation. - Mingfu Liang; Xi Liu; Rong Jin 001; Boyang Liu; Qiuling Suo; Qinghai Zhou; Song Zhou; Laming Chen; Hua Zheng; Zhiyuan Li; Shali Jiang 003; Jiyan Yang; et al. (CoRR, 2025)

Enhancing Embedding Representation Stability in Recommendation Systems with Semantic ID. - Carolina Zheng; Minhui Huang; Dmitrii Pedchenko; Kaushik Rangadurai; Siyu Wang; Gaby Nahum; Jie Lei; Yang Yang; Tao Liu; Zutian Luo; Xiaohan Wei; Dinesh Ramasamy; et al. (CoRR, 2025)