Richard Y. Zhang

Orcid: 0000-0003-3980-2791

Affiliations:
  • University of Illinois at Urbana-Champaign, IL, USA


According to our database1, Richard Y. Zhang authored at least 35 papers between 2015 and 2023.

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

Timeline

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Bibliography

2023
Preconditioned Gradient Descent for Overparameterized Nonconvex Burer-Monteiro Factorization with Global Optimality Certification.
J. Mach. Learn. Res., 2023

Statistically Optimal K-means Clustering via Nonnegative Low-rank Semidefinite Programming.
CoRR, 2023

Fast and Minimax Optimal Estimation of Low-Rank Matrices via Non-Convex Gradient Descent.
CoRR, 2023

Tight Certification of Adversarially Trained Neural Networks via Nonconvex Low-Rank Semidefinite Relaxations.
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.
CoRR, 2022

Simple Alternating Minimization Provably Solves Complete Dictionary Learning.
CoRR, 2022

Accelerating SGD for Highly Ill-Conditioned Huge-Scale Online Matrix Completion.
CoRR, 2022

Improved Global Guarantees for the Nonconvex Burer-Monteiro Factorization via Rank Overparameterization.
CoRR, 2022

Accelerating SGD for Highly Ill-Conditioned Huge-Scale Online Matrix Completion.
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.
IEEE Trans. Control. Netw. Syst., 2021

Sparse semidefinite programs with guaranteed near-linear time complexity via dualized clique tree conversion.
Math. Program., 2021

Sharp Global Guarantees for Nonconvex Low-Rank Matrix Recovery in the Overparameterized Regime.
CoRR, 2021

Preconditioned Gradient Descent for Over-Parameterized Nonconvex Matrix Factorization.
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.
IEEE Trans. Control. Netw. Syst., 2020

How Many Samples is a Good Initial Point Worth?
CoRR, 2020

How many samples is a good initial point worth in Low-rank Matrix Recovery?
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.
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.
IEEE Trans. Control. Netw. Syst., 2019

Sharp Restricted Isometry Bounds for the Inexistence of Spurious Local Minima in Nonconvex Matrix Recovery.
J. Mach. Learn. Res., 2019

Conic optimization for control, energy systems, and machine learning: Applications and algorithms.
Annu. Rev. Control., 2019

Linear-Time Algorithm for Learning Large-Scale Sparse Graphical Models.
IEEE Access, 2019

Monotonicity Between Phase Angles and Power Flow and Its Implications for the Uniqueness of Solutions.
Proceedings of the 52nd Hawaii International Conference on System Sciences, 2019

2018
GMRES-Accelerated ADMM for Quadratic Objectives.
SIAM J. Optim., 2018

How Much Restricted Isometry is Needed In Nonconvex Matrix Recovery?
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.
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.
Proceedings of the 35th International Conference on Machine Learning, 2018

Spurious Critical Points in Power System State Estimation.
Proceedings of the 51st Hawaii International Conference on System Sciences, 2018

Sparse Inverse Covariance Estimation for Chordal Structures.
Proceedings of the 16th European Control Conference, 2018

Efficient Algorithm for Large-and-Sparse LMI Feasibility Problems.
Proceedings of the 57th IEEE Conference on Decision and Control, 2018

Sparse Semidefinite Programs with Near-Linear Time Complexity.
Proceedings of the 57th IEEE Conference on Decision and Control, 2018

Conic Approximation with Provable Guarantee for Traffic Signal Offset Optimization.
Proceedings of the 57th IEEE Conference on Decision and Control, 2018

Conic Optimization Theory: Convexification Techniques and Numerical Algorithms.
Proceedings of the 2018 Annual American Control Conference, 2018

2017
Robust stability analysis for large-scale power systems.
PhD thesis, 2017

Modified interior-point method for large-and-sparse low-rank semidefinite programs.
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.
Proc. IEEE, 2015


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