Regularized robust estimation of mean and covariance matrix under heavy tails and outliers. - Ying Sun 003; Prabhu Babu; Daniel Pérez Palomar (SAM, 2014)

Regularized Tyler's Scatter Estimator: Existence, Uniqueness, and Algorithms. - Ying Sun 003; Prabhu Babu; Daniel P. Palomar (IEEE Trans. Signal Process., 2014)

Robust estimation of structured covariance matrix for heavy-tailed distributions. - Ying Sun 003; Prabhu Babu; Daniel Pérez Palomar (ICASSP, 2015)

Regularized Robust Estimation of Mean and Covariance Matrix Under Heavy-Tailed Distributions. - Ying Sun 003; Prabhu Babu; Daniel Pérez Palomar (IEEE Trans. Signal Process., 2015)

Robust rank constrained kronecker covariance matrix estimation. - Arnaud Breloy; Ying Sun 003; Prabhu Babu; Guillaume Ginolhac; Daniel Pérez Palomar (ACSSC, 2016)

Distributed nonconvex multiagent optimization over time-varying networks. - Ying Sun 003; Gesualdo Scutari; Daniel Pérez Palomar (ACSSC, 2016)

Block majorization-minimization algorithms for low-rank clutter subspace estimation. - Arnaud Breloy; Ying Sun 003; Prabhu Babu; Daniel Pérez Palomar (EUSIPCO, 2016)

Orthogonal sparse eigenvectors: A procrustes problem. - Konstantinos Benidis; Ying Sun 003; Prabhu Babu; Daniel Pérez Palomar (ICASSP, 2016)

A robust signal subspace estimator. - Arnaud Breloy; Ying Sun 003; Prabhu Babu; Guillaume Ginolhac; Daniel Pérez Palomar; Frédéric Pascal 001 (SSP, 2016)

Orthogonal Sparse PCA and Covariance Estimation via Procrustes Reformulation. - Konstantinos Benidis; Ying Sun 003; Prabhu Babu; Daniel P. Palomar (IEEE Trans. Signal Process., 2016)

Low-Complexity Algorithms for Low Rank Clutter Parameters Estimation in Radar Systems. - Ying Sun 003; Arnaud Breloy; Prabhu Babu; Daniel P. Palomar; Frédéric Pascal 001; Guillaume Ginolhac (IEEE Trans. Signal Process., 2016)

Robust Estimation of Structured Covariance Matrix for Heavy-Tailed Elliptical Distributions. - Ying Sun 003; Prabhu Babu; Daniel Pérez Palomar (IEEE Trans. Signal Process., 2016)

Distributed big-data optimization via block communications. - Ivano Notarnicola; Ying Sun 003; Gesualdo Scutari; Giuseppe Notarstefano (CAMSAP, 2017)

Distributed big-data optimization via block-iterative convexification and averaging. - Ivano Notarnicola; Ying Sun 003; Gesualdo Scutari; Giuseppe Notarstefano (CDC, 2017)

D2L: Decentralized dictionary learning over dynamic networks. - Amir Daneshmand; Ying Sun 003; Gesualdo Scutari; Francisco Facchinei (ICASSP, 2017)

Distributed nonconvex optimization for sparse representation. - Ying Sun 003; Gesualdo Scutari (ICASSP, 2017)

Majorization-Minimization Algorithms in Signal Processing, Communications, and Machine Learning. - Ying Sun 003; Prabhu Babu; Daniel P. Palomar (IEEE Trans. Signal Process., 2017)

ASY-SONATA: Achieving Linear Convergence in Distributed Asynchronous Multiagent Optimization. - Ye Tian 021; Ying Sun 003; Gesualdo Scutari (Allerton, 2018)

ASY-SONATA: Achieving Geometric Convergence for Distributed Asynchronous Optimization. - Ye Tian 021; Ying Sun 003; Bin Du; Gesualdo Scutari (CoRR, 2018)

Parallel and Distributed Successive Convex Approximation Methods for Big-Data Optimization. - Gesualdo Scutari; Ying Sun 003 (CoRR, 2018)

Distributed Big-Data Optimization via Block-wise Gradient Tracking. - Ivano Notarnicola; Ying Sun 003; Gesualdo Scutari; Giuseppe Notarstefano (CoRR, 2018)

A Unified Contraction Analysis of a Class of Distributed Algorithms for Composite Optimization. - Jinming Xu 002; Ying Sun 003; Ye Tian 021; Gesualdo Scutari (CAMSAP, 2019)

Convergence Rate of Distributed Optimization Algorithms Based on Gradient Tracking. - Ying Sun 003; Amir Daneshmand; Gesualdo Scutari (CoRR, 2019)

Decentralized Dictionary Learning Over Time-Varying Digraphs. - Amir Daneshmand; Ying Sun 003; Gesualdo Scutari; Francisco Facchinei; Brian M. Sadler (J. Mach. Learn. Res., 2019)

Distributed nonconvex constrained optimization over time-varying digraphs. - Gesualdo Scutari; Ying Sun 003 (Math. Program., 2019)

Accelerated Primal-Dual Algorithms for Distributed Smooth Convex Optimization over Networks. - Jinming Xu 002; Ye Tian 021; Ying Sun 003; Gesualdo Scutari (AISTATS, 2020)

A Unified Algorithmic Framework for Distributed Composite Optimization. - Jinming Xu 002; Ye Tian 021; Ying Sun 003; Gesualdo Scutari (CDC, 2020)

Distributed Algorithms for Composite Optimization: Unified and Tight Convergence Analysis. - Jinming Xu 002; Ye Tian 021; Ying Sun 003; Gesualdo Scutari (CoRR, 2020)

Robust and Secure Wireless Communications via Intelligent Reflecting Surfaces. - Xianghao Yu; Dongfang Xu; Ying Sun 003; Derrick Wing Kwan Ng; Robert Schober (IEEE J. Sel. Areas Commun., 2020)

Achieving Linear Convergence in Distributed Asynchronous Multiagent Optimization. - Ye Tian 021; Ying Sun 003; Gesualdo Scutari (IEEE Trans. Autom. Control., 2020)

Distributed Big-Data Optimization via Blockwise Gradient Tracking. - Ivano Notarnicola; Ying Sun 003; Gesualdo Scutari; Giuseppe Notarstefano (IEEE Trans. Autom. Control., 2021)

Majorization-Minimization on the Stiefel Manifold With Application to Robust Sparse PCA. - Arnaud Breloy; Sandeep Kumar 005; Ying Sun 003; Daniel P. Palomar (IEEE Trans. Signal Process., 2021)

Distributed Algorithms for Composite Optimization: Unified Framework and Convergence Analysis. - Jinming Xu 002; Ye Tian 021; Ying Sun 003; Gesualdo Scutari (IEEE Trans. Signal Process., 2021)

Tackling Data Heterogeneity: A New Unified Framework for Decentralized SGD with Sample-induced Topology. - Yan Huang 036; Ying Sun 003; Zehan Zhu; Changzhi Yan; Jinming Xu 002 (ICML, 2022)

High-Dimensional Inference over Networks: Linear Convergence and Statistical Guarantees. - Ying Sun 003; Marie Maros; Gesualdo Scutari; Guang Cheng (CoRR, 2022)

Distributed Optimization Based on Gradient Tracking Revisited: Enhancing Convergence Rate via Surrogation. - Ying Sun 003; Gesualdo Scutari; Amir Daneshmand (SIAM J. Optim., 2022)

A Loopless Distributed Algorithm for Personalized Bilevel Optimization. - Youcheng Niu; Ying Sun 003; Yan Huang 036; Jinming Xu 002 (CDC, 2023)

Distributed Stochastic Bilevel Optimization: Improved Complexity and Heterogeneity Analysis. - Youcheng Niu; Jinming Xu 002; Ying Sun 003; Yan Huang 036; Li Chai 008 (CoRR, 2023)

Distributed Sparse Regression via Penalization. - Yao Ji; Gesualdo Scutari; Ying Sun 003; Harsha Honnappa (J. Mach. Learn. Res., 2023)

Distributed (ATC) Gradient Descent for High Dimension Sparse Regression. - Yao Ji; Gesualdo Scutari; Ying Sun 003; Harsha Honnappa (IEEE Trans. Inf. Theory, 2023)

EFSkip: A New Error Feedback with Linear Speedup for Compressed Federated Learning with Arbitrary Data Heterogeneity. - Hongyan Bao; Pengwen Chen; Ying Sun 003; Zhize Li (AAAI, 2025)

The Effectiveness of Local Updates for Decentralized Learning Under Data Heterogeneity. - Tongle Wu; Zhize Li; Ying Sun 003 (IEEE Trans. Signal Process., 2025)