MATCHA: Speeding Up Decentralized SGD via Matching Decomposition Sampling. - Jianyu Wang 019; Anit Kumar Sahu; Zhouyi Yang; Gauri Joshi; Soummya Kar (CoRR, 2019)

Exploring the Error-Runtime Trade-off in Decentralized Optimization. - Jianyu Wang 019; Anit Kumar Sahu; Gauri Joshi; Soummya Kar (ACSSC, 2020)

Machine Learning on Volatile Instances. - Xiaoxi Zhang 001; Jianyu Wang 019; Gauri Joshi; Carlee Joe-Wong (INFOCOM, 2020)

Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization. - Jianyu Wang 019; Qinghua Liu; Hao Liang 002; Gauri Joshi; H. Vincent Poor (NeurIPS, 2020)

Slow and Stale Gradients Can Win the Race. - Sanghamitra Dutta; Jianyu Wang 019; Gauri Joshi (IEEE J. Sel. Areas Inf. Theory, 2021)

A Novel Framework for the Analysis and Design of Heterogeneous Federated Learning. - Jianyu Wang 019; Qinghua Liu; Hao Liang 002; Gauri Joshi; H. Vincent Poor (IEEE Trans. Signal Process., 2021)

Machine Learning on Volatile Instances: Convergence, Runtime, and Cost Tradeoffs. - Xiaoxi Zhang 001; Jianyu Wang 019; Li-Feng Lee; Tom Yang; Akansha Kalra; Gauri Joshi; Carlee Joe-Wong (IEEE/ACM Trans. Netw., 2022)

Matcha: A Matching-Based Link Scheduling Strategy to Speed up Distributed Optimization. - Jianyu Wang 019; Anit Kumar Sahu; Gauri Joshi; Soummya Kar (IEEE Trans. Signal Process., 2022)

FedDisco: Federated Learning with Discrepancy-Aware Collaboration. - Rui Ye 001; Mingkai Xu; Jianyu Wang 019; Chenxin Xu; Siheng Chen; Yanfeng Wang 001 (ICML, 2023)

FedFM: Anchor-Based Feature Matching for Data Heterogeneity in Federated Learning. - Rui Ye 001; Zhenyang Ni; Chenxin Xu; Jianyu Wang 019; Siheng Chen; Yonina C. Eldar (IEEE Trans. Signal Process., 2023)

Communication-Efficient and Model-Heterogeneous Personalized Federated Learning via Clustered Knowledge Transfer. - Yae Jee Cho; Jianyu Wang 019; Tarun Chirvolu; Gauri Joshi (IEEE J. Sel. Top. Signal Process., 2023)