2025
The Effectiveness of Local Updates for Decentralized Learning Under Data Heterogeneity.
IEEE Trans. Signal Process., 2025
EFSkip: A New Error Feedback with Linear Speedup for Compressed Federated Learning with Arbitrary Data Heterogeneity.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025
2023
Distributed (ATC) Gradient Descent for High Dimension Sparse Regression.
IEEE Trans. Inf. Theory, August, 2023
Distributed Sparse Regression via Penalization.
J. Mach. Learn. Res., 2023
Distributed Stochastic Bilevel Optimization: Improved Complexity and Heterogeneity Analysis.
CoRR, 2023
A Loopless Distributed Algorithm for Personalized Bilevel Optimization.
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023
2022
Distributed Optimization Based on Gradient Tracking Revisited: Enhancing Convergence Rate via Surrogation.
SIAM J. Optim., 2022
High-Dimensional Inference over Networks: Linear Convergence and Statistical Guarantees.
CoRR, 2022
Tackling Data Heterogeneity: A New Unified Framework for Decentralized SGD with Sample-induced Topology.
Proceedings of the International Conference on Machine Learning, 2022
2021
Distributed Algorithms for Composite Optimization: Unified Framework and Convergence Analysis.
IEEE Trans. Signal Process., 2021
Majorization-Minimization on the Stiefel Manifold With Application to Robust Sparse PCA.
IEEE Trans. Signal Process., 2021
Distributed Big-Data Optimization via Blockwise Gradient Tracking.
IEEE Trans. Autom. Control., 2021
2020
Achieving Linear Convergence in Distributed Asynchronous Multiagent Optimization.
IEEE Trans. Autom. Control., 2020
Robust and Secure Wireless Communications via Intelligent Reflecting Surfaces.
IEEE J. Sel. Areas Commun., 2020
Distributed Algorithms for Composite Optimization: Unified and Tight Convergence Analysis.
CoRR, 2020
A Unified Algorithmic Framework for Distributed Composite Optimization.
Proceedings of the 59th IEEE Conference on Decision and Control, 2020
Accelerated Primal-Dual Algorithms for Distributed Smooth Convex Optimization over Networks.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
2019
Distributed nonconvex constrained optimization over time-varying digraphs.
Math. Program., 2019
Decentralized Dictionary Learning Over Time-Varying Digraphs.
J. Mach. Learn. Res., 2019
Convergence Rate of Distributed Optimization Algorithms Based on Gradient Tracking.
CoRR, 2019
A Unified Contraction Analysis of a Class of Distributed Algorithms for Composite Optimization.
Proceedings of the 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2019
2018
Distributed Big-Data Optimization via Block-wise Gradient Tracking.
CoRR, 2018
Parallel and Distributed Successive Convex Approximation Methods for Big-Data Optimization.
CoRR, 2018
ASY-SONATA: Achieving Geometric Convergence for Distributed Asynchronous Optimization.
CoRR, 2018
ASY-SONATA: Achieving Linear Convergence in Distributed Asynchronous Multiagent Optimization.
Proceedings of the 56th Annual Allerton Conference on Communication, 2018
2017
Majorization-Minimization Algorithms in Signal Processing, Communications, and Machine Learning.
IEEE Trans. Signal Process., 2017
Distributed nonconvex optimization for sparse representation.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017
D2L: Decentralized dictionary learning over dynamic networks.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017
Distributed big-data optimization via block-iterative convexification and averaging.
Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017
Distributed big-data optimization via block communications.
Proceedings of the 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2017
2016
Robust Estimation of Structured Covariance Matrix for Heavy-Tailed Elliptical Distributions.
IEEE Trans. Signal Process., 2016
Low-Complexity Algorithms for Low Rank Clutter Parameters Estimation in Radar Systems.
IEEE Trans. Signal Process., 2016
Orthogonal Sparse PCA and Covariance Estimation via Procrustes Reformulation.
IEEE Trans. Signal Process., 2016
A robust signal subspace estimator.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2016
Orthogonal sparse eigenvectors: A procrustes problem.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016
Block majorization-minimization algorithms for low-rank clutter subspace estimation.
Proceedings of the 24th European Signal Processing Conference, 2016
Distributed nonconvex multiagent optimization over time-varying networks.
Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016
Robust rank constrained kronecker covariance matrix estimation.
Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016
2015
Regularized Robust Estimation of Mean and Covariance Matrix Under Heavy-Tailed Distributions.
IEEE Trans. Signal Process., 2015
Robust estimation of structured covariance matrix for heavy-tailed distributions.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015
2014
Regularized Tyler's Scatter Estimator: Existence, Uniqueness, and Algorithms.
IEEE Trans. Signal Process., 2014
Regularized robust estimation of mean and covariance matrix under heavy tails and outliers.
Proceedings of the IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, 2014