Richard Y. Zhang

According to our database, Richard Y. Zhang authored at least 36 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Statistically Optimal K-means Clustering via Nonnegative Low-rank Semidefinite Programming.

Yubo Zhuang, Xiaohui Chen, Yun Yang, Richard Y. Zhang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Fast and Accurate Estimation of Low-Rank Matrices from Noisy Measurements via Preconditioned Non-Convex Gradient Descent.

Jialun Zhang, Richard Y. Zhang, Hong-Ming Chiu

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Preconditioned Gradient Descent for Overparameterized Nonconvex Burer-Monteiro Factorization with Global Optimality Certification.

Gavin Zhang, Salar Fattahi, Richard Y. Zhang

J. Mach. Learn. Res., 2023

Fast and Minimax Optimal Estimation of Low-Rank Matrices via Non-Convex Gradient Descent.

Gavin Zhang, Hong-Ming Chiu, Richard Y. Zhang

CoRR, 2023

Tight Certification of Adversarially Trained Neural Networks via Nonconvex Low-Rank Semidefinite Relaxations.

Hong-Ming Chiu, Richard Y. Zhang

Proceedings of the International Conference on Machine Learning, 2023

2022

Overcoming the Convex Relaxation Barrier for Neural Network Verification via Nonconvex Low-Rank Semidefinite Relaxations.

Hong-Ming Chiu, Richard Y. Zhang

CoRR, 2022

Simple Alternating Minimization Provably Solves Complete Dictionary Learning.

Geyu Liang, Gavin Zhang, Salar Fattahi, Richard Y. Zhang

CoRR, 2022

Accelerating SGD for Highly Ill-Conditioned Huge-Scale Online Matrix Completion.

Gavin Zhang, Hong-Ming Chiu, Richard Y. Zhang

CoRR, 2022

Improved Global Guarantees for the Nonconvex Burer-Monteiro Factorization via Rank Overparameterization.

Richard Y. Zhang

CoRR, 2022

Accelerating SGD for Highly Ill-Conditioned Huge-Scale Online Matrix Completion.

Jialun Zhang, Hong-Ming Chiu, Richard Y. Zhang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Uniqueness of Power Flow Solutions Using Monotonicity and Network Topology.

SangWoo Park, Richard Y. Zhang, Javad Lavaei, Ross Baldick

IEEE Trans. Control. Netw. Syst., 2021

Sparse semidefinite programs with guaranteed near-linear time complexity via dualized clique tree conversion.

Richard Y. Zhang, Javad Lavaei

Math. Program., 2021

Sharp Global Guarantees for Nonconvex Low-Rank Matrix Recovery in the Overparameterized Regime.

Richard Y. Zhang

CoRR, 2021

Preconditioned Gradient Descent for Over-Parameterized Nonconvex Matrix Factorization.

Jialun Zhang, Salar Fattahi, Richard Y. Zhang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Large-Scale Traffic Signal Offset Optimization.

Yi Ouyang, Richard Y. Zhang, Javad Lavaei, Pravin Varaiya

IEEE Trans. Control. Netw. Syst., 2020

How Many Samples is a Good Initial Point Worth?

Gavin Zhang, Richard Y. Zhang

CoRR, 2020

How many samples is a good initial point worth in Low-rank Matrix Recovery?

Jialun Zhang, Richard Y. Zhang

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

On the Tightness of Semidefinite Relaxations for Certifying Robustness to Adversarial Examples.

Richard Y. Zhang

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Spurious Local Minima in Power System State Estimation.

Richard Y. Zhang, Javad Lavaei, Ross Baldick

IEEE Trans. Control. Netw. Syst., 2019

Sharp Restricted Isometry Bounds for the Inexistence of Spurious Local Minima in Nonconvex Matrix Recovery.

Richard Y. Zhang, Somayeh Sojoudi, Javad Lavaei

J. Mach. Learn. Res., 2019

Conic optimization for control, energy systems, and machine learning: Applications and algorithms.

Richard Y. Zhang, Cédric Josz, Somayeh Sojoudi

Annu. Rev. Control., 2019

Linear-Time Algorithm for Learning Large-Scale Sparse Graphical Models.

Salar Fattahi, Richard Y. Zhang, Somayeh Sojoudi

IEEE Access, 2019

Monotonicity Between Phase Angles and Power Flow and Its Implications for the Uniqueness of Solutions.

Sangwoo Park, Richard Y. Zhang, Javad Lavaei, Ross Baldick

Proceedings of the 52nd Hawaii International Conference on System Sciences, 2019

2018

GMRES-Accelerated ADMM for Quadratic Objectives.

Richard Y. Zhang, Jacob K. White

SIAM J. Optim., 2018

How Much Restricted Isometry is Needed In Nonconvex Matrix Recovery?

Richard Y. Zhang, Cédric Josz, Somayeh Sojoudi, Javad Lavaei

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

A theory on the absence of spurious solutions for nonconvex and nonsmooth optimization.

Cédric Josz, Yi Ouyang, Richard Y. Zhang, Javad Lavaei, Somayeh Sojoudi

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Large-Scale Sparse Inverse Covariance Estimation via Thresholding and Max-Det Matrix Completion.

Richard Y. Zhang, Salar Fattahi, Somayeh Sojoudi

Proceedings of the 35th International Conference on Machine Learning, 2018

Spurious Critical Points in Power System State Estimation.

Richard Y. Zhang, Javad Lavaei, Ross Baldick

Proceedings of the 51st Hawaii International Conference on System Sciences, 2018

Sparse Inverse Covariance Estimation for Chordal Structures.

Salar Fattahi, Richard Y. Zhang, Somayeh Sojoudi

Proceedings of the 16th European Control Conference, 2018

Efficient Algorithm for Large-and-Sparse LMI Feasibility Problems.

Richard Y. Zhang, Javad Lavaei

Proceedings of the 57th IEEE Conference on Decision and Control, 2018

Sparse Semidefinite Programs with Near-Linear Time Complexity.

Richard Y. Zhang, Javad Lavaei

Proceedings of the 57th IEEE Conference on Decision and Control, 2018

Conic Approximation with Provable Guarantee for Traffic Signal Offset Optimization.

Yi Ouyang, Richard Y. Zhang, Javad Lavaei, Pravin Varaiya

Proceedings of the 57th IEEE Conference on Decision and Control, 2018

Conic Optimization Theory: Convexification Techniques and Numerical Algorithms.

Richard Y. Zhang, Cédric Josz, Somayeh Sojoudi

Proceedings of the 2018 Annual American Control Conference, 2018

2017

Robust stability analysis for large-scale power systems.

Richard Yi Zhang

PhD thesis, 2017

Modified interior-point method for large-and-sparse low-rank semidefinite programs.

Richard Y. Zhang, Javad Lavaei

Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017

2015

Toeplitz-Plus-Hankel Matrix Recovery for Green's Function Computations on General Substrates.

Richard Y. Zhang, Jacob K. White

Proc. IEEE, 2015