Proximal Subgradient Norm Minimization of ISTA and FISTA, Applied and Computational Harmonic Analysis, 2025, Published Online.
Bowen Li, Bin Shi and Ya-xiang Yuan
Revisiting Nesterov's acceleration via high-resolution differential equations, Journal of Global Optimization, 93:551-569, 2025.
Shuo Chen, Bin Shi and Ya-xiang Yuan
A Lyapunov Analysis of Accelerated PDHG Algorithms, Journal of Optimization Theory and Applications, 207(67):1-20, 2025.
Xueying Zeng and Bin Shi
Numerical Solution for Nonlinear 4D Variational Data Assimilation (4D-Var) via ADMM, [code], Journal of Computational Physics, 538:114163, 2025.
Bowen Li and Bin Shi
Linear Convergence of ISTA and FISTA, Journal of the Operations Research Society of China, 2024, Published online.
On the Hyperparameters in Stochastic Gradient Descent with Momentum, Journal of Machine Learning Research, 25(236):1-40, 2024.
Bin Shi
Linear Convergence of Forward-Backward Accelerated Algorithms without Knowledge of the Modulus of Strong Convexity, SIAM Journal on Optimization, 34(2):2150-2168, 2024.
The sampling method for optimal precursors of El Niño-Southern Oscillation events, Nonlinear Processes in Geophysics, 31(1):165–174, 2024.
Bin Shi and Junjie Ma
On Learning Rates and Schrödinger Operators, Journal of Machine Learning Research, 24(379):1-53, 2023.
Bin Shi, Weijie Su and Michael I. Jordan
An adjoint-free algorithm for conditional nonlinear optimal perturbations (CNOPs) via sampling, Nonlinear Processes in Geophysics, 30(3):263–276, 2023.
Bin Shi and Guodong Sun
Understanding the Acceleration Phenomenon via High-Resolution Differential Equations, Mathematical Programming, Series A, 195:79–148, 2022.
Bin Shi, Simon S. Du, Weijie Su and Michael I. Jordan
Conjugate and Cut Points in Ideal Fluid Motion, Annales Mathématiques du Québec, 46(1):207-225, 2022.
Theodore D. Drivas, Gerard Misiołek, Bin Shi and Tsuyoshi Yoneda
Quantum Optimization via Gradient-Based Hamiltonian Descent, [code], ICML 2025.
Jiaqi Leng, Bin Shi
Acceleration via Symplectic Discretization of High-Resolution Differential Equations, NeurIPS 2019.
Bin Shi, Simon S. Du, Weijie J. Su and Michael I. Jordan
A Conservation Law Method in Optimization, The Tenth Workshop on Optimization for Machine Learning, OptML Workshop, NeurIPS 2017./
Bin Shi, Tao Li and Sundaraja S. Iyengar
Mathematical Theories of Machine Learning - Theory and Applications, Springer International Publishing, 2020.
Bin Shi and Sundaraja S. Iyengar
Gradient Norm Minimization of Nesterov's Acceleration o(1/k^3),
Optimal Disturbances of Blocking: A Barotropic View,
Bin Shi, Dehai Luo and Wenqi Zhang
On Underdamped Nesterov's Acceleration,
Understanding the ADMM Algorithm via High-Resolution Differential Equations,
Understanding the PDHG Algorithm via High-Resolution Differential Equations,
Lyapunov Analysis For Monotonically Forward-Backward Accelerated Algorithms,
Mingwei Fu and Bin Shi
A Family of Controllable Momentum Coefficients for Forward-Backward Accelerated Algorithms,
On Pseudospectral Concentration for Rank-1 Sampling,
Kuo Gai and Bin Shi