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ORCIDRichard Y. Zhang
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- affiliation: University of Illinois at Urbana-Champaign, IL, USA
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2020 – today
- 2025
[c19]Palash Sashittal
, Richard Y. Zhang, Benjamin K. Law, Henri Schmidt, Alexander Strzalkowski, Adriano Bolondi, Michelle M. Chan, Benjamin J. Raphael:
Inferring Cell Differentiation Maps from Lineage Tracing Data. RECOMB 2025: 312-315- [i15]Gavin Zhang, Salar Fattahi, Richard Y. Zhang:
Preconditioned Gradient Descent for Over-Parameterized Nonconvex Matrix Factorization. CoRR abs/2504.09708 (2025) - 2024
- [c18]Jialun Zhang, Richard Y. Zhang, Hong-Ming Chiu:
Fast and Accurate Estimation of Low-Rank Matrices from Noisy Measurements via Preconditioned Non-Convex Gradient Descent. AISTATS 2024: 3772-3780 - [c17]Yubo Zhuang, Xiaohui Chen, Yun Yang, Richard Y. Zhang:
Statistically Optimal K-means Clustering via Nonnegative Low-rank Semidefinite Programming. ICLR 2024 - 2023
- [j10]Gavin Zhang, Salar Fattahi, Richard Y. Zhang:
Preconditioned Gradient Descent for Overparameterized Nonconvex Burer-Monteiro Factorization with Global Optimality Certification. J. Mach. Learn. Res. 24: 163:1-163:55 (2023) - [c16]Hong-Ming Chiu, Richard Y. Zhang:
Tight Certification of Adversarially Trained Neural Networks via Nonconvex Low-Rank Semidefinite Relaxations. ICML 2023: 5631-5660 - [i14]Gavin Zhang, Hong-Ming Chiu, Richard Y. Zhang:
Fast and Minimax Optimal Estimation of Low-Rank Matrices via Non-Convex Gradient Descent. CoRR abs/2305.17224 (2023) - [i13]Yubo Zhuang, Xiaohui Chen, Yun Yang, Richard Y. Zhang:
Statistically Optimal K-means Clustering via Nonnegative Low-rank Semidefinite Programming. CoRR abs/2305.18436 (2023) - 2022
- [c15]Jialun Zhang, Hong-Ming Chiu, Richard Y. Zhang:
Accelerating SGD for Highly Ill-Conditioned Huge-Scale Online Matrix Completion. NeurIPS 2022 - [i12]Gavin Zhang, Salar Fattahi, Richard Y. Zhang:
Preconditioned Gradient Descent for Overparameterized Nonconvex Burer-Monteiro Factorization with Global Optimality Certification. CoRR abs/2206.03345 (2022) - [i11]Richard Y. Zhang:
Improved Global Guarantees for the Nonconvex Burer-Monteiro Factorization via Rank Overparameterization. CoRR abs/2207.01789 (2022) - [i10]Gavin Zhang, Hong-Ming Chiu, Richard Y. Zhang:
Accelerating SGD for Highly Ill-Conditioned Huge-Scale Online Matrix Completion. CoRR abs/2208.11246 (2022) - [i9]Geyu Liang, Gavin Zhang, Salar Fattahi, Richard Y. Zhang:
Simple Alternating Minimization Provably Solves Complete Dictionary Learning. CoRR abs/2210.12816 (2022) - [i8]Hong-Ming Chiu, Richard Y. Zhang:
Overcoming the Convex Relaxation Barrier for Neural Network Verification via Nonconvex Low-Rank Semidefinite Relaxations. CoRR abs/2211.17244 (2022) - 2021
- [j9]Richard Y. Zhang, Javad Lavaei:
Sparse semidefinite programs with guaranteed near-linear time complexity via dualized clique tree conversion. Math. Program. 188(1): 351-393 (2021) - [j8]SangWoo Park, Richard Y. Zhang, Javad Lavaei, Ross Baldick:
Uniqueness of Power Flow Solutions Using Monotonicity and Network Topology. IEEE Trans. Control. Netw. Syst. 8(1): 319-330 (2021) - [c14]Jialun Zhang, Salar Fattahi, Richard Y. Zhang:
Preconditioned Gradient Descent for Over-Parameterized Nonconvex Matrix Factorization. NeurIPS 2021: 5985-5996 - [i7]Richard Y. Zhang:
Sharp Global Guarantees for Nonconvex Low-Rank Matrix Recovery in the Overparameterized Regime. CoRR abs/2104.10790 (2021) - 2020
- [j7]Yi Ouyang, Richard Y. Zhang, Javad Lavaei, Pravin Varaiya:
Large-Scale Traffic Signal Offset Optimization. IEEE Trans. Control. Netw. Syst. 7(3): 1176-1187 (2020) - [c13]Richard Y. Zhang:
On the Tightness of Semidefinite Relaxations for Certifying Robustness to Adversarial Examples. NeurIPS 2020 - [c12]Jialun Zhang, Richard Y. Zhang:
How many samples is a good initial point worth in Low-rank Matrix Recovery? NeurIPS 2020 - [i6]Richard Y. Zhang:
On the Tightness of Semidefinite Relaxations for Certifying Robustness to Adversarial Examples. CoRR abs/2006.06759 (2020) - [i5]Gavin Zhang, Richard Y. Zhang:
How Many Samples is a Good Initial Point Worth? CoRR abs/2006.06915 (2020)
2010 – 2019
- 2019
- [j6]Salar Fattahi, Richard Y. Zhang, Somayeh Sojoudi:
Linear-Time Algorithm for Learning Large-Scale Sparse Graphical Models. IEEE Access 7: 12658-12672 (2019) - [j5]Richard Y. Zhang, Cédric Josz, Somayeh Sojoudi:
Conic optimization for control, energy systems, and machine learning: Applications and algorithms. Annu. Rev. Control. 47: 323-340 (2019) - [j4]Richard Y. Zhang, Somayeh Sojoudi, Javad Lavaei:
Sharp Restricted Isometry Bounds for the Inexistence of Spurious Local Minima in Nonconvex Matrix Recovery. J. Mach. Learn. Res. 20: 114:1-114:34 (2019) - [j3]Richard Y. Zhang, Javad Lavaei, Ross Baldick:
Spurious Local Minima in Power System State Estimation. IEEE Trans. Control. Netw. Syst. 6(3): 1086-1096 (2019) - [c11]Sangwoo Park, Richard Y. Zhang, Javad Lavaei, Ross Baldick:
Monotonicity Between Phase Angles and Power Flow and Its Implications for the Uniqueness of Solutions. HICSS 2019: 1-10 - [i4]Richard Y. Zhang, Somayeh Sojoudi, Javad Lavaei:
Sharp Restricted Isometry Bounds for the Inexistence of Spurious Local Minima in Nonconvex Matrix Recovery. CoRR abs/1901.01631 (2019) - [i3]Yi Ouyang, Richard Y. Zhang, Javad Lavaei, Pravin Varaiya:
Large-Scale Traffic Signal Offset Optimization. CoRR abs/1911.08368 (2019) - 2018
- [j2]Richard Y. Zhang, Jacob K. White:
GMRES-Accelerated ADMM for Quadratic Objectives. SIAM J. Optim. 28(4): 3025-3056 (2018) - [c10]Richard Y. Zhang, Cédric Josz, Somayeh Sojoudi:
Conic Optimization Theory: Convexification Techniques and Numerical Algorithms. ACC 2018: 798-815 - [c9]Yi Ouyang, Richard Y. Zhang, Javad Lavaei, Pravin Varaiya:
Conic Approximation with Provable Guarantee for Traffic Signal Offset Optimization. CDC 2018: 229-236 - [c8]Richard Y. Zhang, Javad Lavaei:
Sparse Semidefinite Programs with Near-Linear Time Complexity. CDC 2018: 1624-1631 - [c7]Richard Y. Zhang, Javad Lavaei:
Efficient Algorithm for Large-and-Sparse LMI Feasibility Problems. CDC 2018: 6868-6875 - [c6]Salar Fattahi, Richard Y. Zhang, Somayeh Sojoudi:
Sparse Inverse Covariance Estimation for Chordal Structures. ECC 2018: 837-844 - [c5]Richard Y. Zhang, Javad Lavaei, Ross Baldick:
Spurious Critical Points in Power System State Estimation. HICSS 2018: 1-10 - [c4]Richard Y. Zhang, Salar Fattahi, Somayeh Sojoudi:
Large-Scale Sparse Inverse Covariance Estimation via Thresholding and Max-Det Matrix Completion. ICML 2018: 5761-5770 - [c3]Cédric Josz, Yi Ouyang, Richard Y. Zhang, Javad Lavaei, Somayeh Sojoudi:
A theory on the absence of spurious solutions for nonconvex and nonsmooth optimization. NeurIPS 2018: 2446-2454 - [c2]Richard Y. Zhang, Cédric Josz, Somayeh Sojoudi, Javad Lavaei:
How Much Restricted Isometry is Needed In Nonconvex Matrix Recovery? NeurIPS 2018: 5591-5602 - [i2]Richard Y. Zhang, Salar Fattahi, Somayeh Sojoudi:
Linear-Time Algorithm for Learning Large-Scale Sparse Graphical Models. CoRR abs/1802.04911 (2018) - [i1]Richard Y. Zhang, Cédric Josz, Somayeh Sojoudi, Javad Lavaei:
How Much Restricted Isometry is Needed In Nonconvex Matrix Recovery? CoRR abs/1805.10251 (2018) - 2017
- [b1]Richard Yi Zhang:
Robust stability analysis for large-scale power systems. Massachusetts Institute of Technology, Cambridge, USA, 2017 - [c1]Richard Y. Zhang, Javad Lavaei:
Modified interior-point method for large-and-sparse low-rank semidefinite programs. CDC 2017: 5640-5647 - 2015
- [j1]Richard Y. Zhang, Jacob K. White:
Toeplitz-Plus-Hankel Matrix Recovery for Green's Function Computations on General Substrates. Proc. IEEE 103(11): 1970-1984 (2015)
Coauthor Index
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