Ying Sun

Orcid: 0000-0002-9709-6509

Affiliations:
  • Purdue University, School of Industrial Engineering, West-Lafayette, IN, USA
  • Hong Kong University of Science and Technology, Department of Electronic and Computer Engineering, Hong Kong (former)


According to our database1, Ying Sun authored at least 40 papers between 2014 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

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


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