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Siqi Zhang
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Biased stochastic first-order methods for conditional stochastic optimization and applications in meta learning
Y Hu, S Zhang, X Chen, N He
Advances in Neural Information Processing Systems 33, 2759-2770, 2020
95*2020
The complexity of nonconvex-strongly-concave minimax optimization
S Zhang, J Yang, C Guzmán, N Kiyavash, N He
Uncertainty in Artificial Intelligence, 482-492, 2021
792021
On the convergence rate of stochastic mirror descent for nonsmooth nonconvex optimization
S Zhang, N He
arXiv preprint arXiv:1806.04781, 2018
672018
A catalyst framework for minimax optimization
J Yang, S Zhang, N Kiyavash, N He
Advances in Neural Information Processing Systems 33, 5667-5678, 2020
632020
Generalization Bounds of Nonconvex-(Strongly)-Concave Stochastic Minimax Optimization
S Zhang, Y Hu, L Zhang, N He
International Conference on Artificial Intelligence and Statistics, 694-702, 2024
7*2024
Communication-efficient gradient descent-accent methods for distributed variational inequalities: Unified analysis and local updates
S Zhang, S Choudhury, SU Stich, N Loizou
arXiv preprint arXiv:2306.05100, 2023
52023
First-Order Optimization Inspired from Finite-Time Convergent Flows
S Zhang, M Benosman, O Romero, A Cherian
arXiv preprint arXiv:2010.02990, 2020
4*2020
Exploitable structures and complexities of modern nonconvex optimization: Fundamental limits and efficient algorithms
S Zhang
University of Illinois at Urbana-Champaign, 2022
2022
ProxSkip for Stochastic Variational Inequalities: A Federated Learning Algorithm for Provable Communication Acceleration
S Zhang, N Loizou
2022
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Articles 1–9