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.
Bowen Li, Bin Shi and Ya-xiang Yuan
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(1):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),
Shuo Chen, Bin Shi and Ya-xiang Yuan
Optimal Disturbances of Blocking: A Barotropic View,
Bin Shi, Dehai Luo and Wenqi Zhang
Proximal Subgradient Norm Minimization of ISTA and FISTA,
Revisiting the acceleration phenomenon via high-resolution differential equations,
On Underdamped Nesterov's Acceleration,
Understanding the ADMM Algorithm via High-Resolution Differential Equations,
Understanding the PDHG Algorithm via High-Resolution Differential Equations,
A Lyapunov Analysis of Accelerated PDHG Algorithms,
Xueying Zeng and Bin Shi
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