Cover Image

A Schrödinger Eigenfunction Method for Long-Horizon Stochastic Optimal Control

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Claeys, Louis, Goldman, Artur, Shen, Zebang, He, Niao
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Hessian-Aware Stochastic Differential Equation for Modelling SGD
by: Li, Xiang, et al.
Published: (2024)

Landing with the Score: Riemannian Optimization through Denoising
by: Kharitenko, Andrey, et al.
Published: (2025)

Optimal Local Convergence Rates of Stochastic First-Order Methods under Local $α$-PL
by: Masiha, Saeed, et al.
Published: (2024)

Biased Stochastic First-Order Methods for Conditional Stochastic Optimization and Applications in Meta Learning
by: Hu, Yifan, et al.
Published: (2020)

Multi-level Monte-Carlo Gradient Methods for Stochastic Optimization with Biased Oracles
by: Hu, Yifan, et al.
Published: (2024)

On the Connectedness of Sublevel Sets in Invex Optimization
by: Thoma, Vinzenz, et al.
Published: (2026)

Primal Methods for Variational Inequality Problems with Functional Constraints
by: Zhang, Liang, et al.
Published: (2024)

Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization
by: Zhang, Liang, et al.
Published: (2023)

TiAda: A Time-scale Adaptive Algorithm for Nonconvex Minimax Optimization
by: Li, Xiang, et al.
Published: (2022)

Superquantile-Gibbs Relaxation for Minima-selection in Bilevel Optimization
by: Masiha, Saeed, et al.
Published: (2025)

From Gradient Clipping to Normalization for Heavy Tailed SGD
by: Hübler, Florian, et al.
Published: (2024)

Linear Convergence of Entropy-Regularized Natural Policy Gradient with Linear Function Approximation
by: Cayci, Semih, et al.
Published: (2021)

Select-then-differentiate: Solving Bilevel Optimization with Manifold Lower-level Solution Sets
by: Masiha, Saeed, et al.
Published: (2026)

Achieving Near-Optimal Convergence for Distributed Minimax Optimization with Adaptive Stepsizes
by: Huang, Yan, et al.
Published: (2024)

A Taxonomy of Loss Functions for Stochastic Optimal Control
by: Domingo-Enrich, Carles
Published: (2024)

Stochastic Auto-conditioned Fast Gradient Methods with Optimal Rates
by: Ji, Yao, et al.
Published: (2026)

When is Mean-Field Reinforcement Learning Tractable and Relevant?
by: Yardim, Batuhan, et al.
Published: (2024)

An Efficient On-Policy Deep Learning Framework for Stochastic Optimal Control
by: Hua, Mengjian, et al.
Published: (2024)

On Policy Stochasticity in Mutual Information Optimal Control of Linear Systems
by: Enami, Shoju, et al.
Published: (2025)

Exploiting Approximate Symmetry for Efficient Multi-Agent Reinforcement Learning
by: Yardim, Batuhan, et al.
Published: (2024)

Rare Event Analysis via Stochastic Optimal Control
by: Du, Yuanqi, et al.
Published: (2026)

Nearly Optimal Linear Convergence of Stochastic Primal-Dual Methods for Linear Programming
by: Lu, Haihao, et al.
Published: (2021)

Adjoint Matching through the Lens of the Stochastic Maximum Principle in Optimal Control
by: Domingo-Enrich, Carles, et al.
Published: (2026)

Stochastic Control for Fine-tuning Diffusion Models: Optimality, Regularity, and Convergence
by: Han, Yinbin, et al.
Published: (2024)

Mutual Information Optimal Density Control of Linear Systems and Generalized Schrödinger Bridges with Reference Refinement
by: Enami, Shoju, et al.
Published: (2026)

Data-Driven Stochastic Optimal Control in Reproducing Kernel Hilbert Spaces
by: Hoischen, Nicolas, et al.
Published: (2024)

Recent Developments in Machine Learning Methods for Stochastic Control and Games
by: Hu, Ruimeng, et al.
Published: (2023)

Adaptive Learning-based Surrogate Method for Stochastic Programs with Implicitly Decision-dependent Uncertainty
by: Shen, Boyang, et al.
Published: (2025)

On the Benefits of Weight Normalization for Overparameterized Matrix Sensing
by: Wei, Yudong, et al.
Published: (2025)

On the Crucial Role of Initialization for Matrix Factorization
by: Li, Bingcong, et al.
Published: (2024)

Optimal Horizon-Free Reward-Free Exploration for Linear Mixture MDPs
by: Zhang, Junkai, et al.
Published: (2023)

Adjoint Matching: Fine-tuning Flow and Diffusion Generative Models with Memoryless Stochastic Optimal Control
by: Domingo-Enrich, Carles, et al.
Published: (2024)

Stochastic Optimal Control Matching
by: Domingo-Enrich, Carles, et al.
Published: (2023)

Zero-Shot Transferable Solution Method for Parametric Optimal Control Problems
by: Li, Xingjian, et al.
Published: (2025)

On the Stability of Nonlinear Receding Horizon Control: A Geometric Perspective
by: Westenbroek, Tyler, et al.
Published: (2021)

Compressed Decentralized Momentum Stochastic Gradient Methods for Nonconvex Optimization
by: Liu, Wei, et al.
Published: (2025)

MDNS: Masked Diffusion Neural Sampler via Stochastic Optimal Control
by: Zhu, Yuchen, et al.
Published: (2025)

A Machine Learning Algorithm for Finite-Horizon Stochastic Control Problems in Economics
by: Peng, Xianhua, et al.
Published: (2024)

Optimal Rates for Robust Stochastic Convex Optimization
by: Gao, Changyu, et al.
Published: (2024)

Optimal Algorithms for Stochastic Complementary Composite Minimization
by: d'Aspremont, Alexandre, et al.
Published: (2022)