:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Lam, Samuel Chun-Hei, Sirignano, Justin, Wang, Ziheng
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Optimization and Control Probability
Online Access:	https://arxiv.org/abs/2403.16825
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Convergence of Actor-Critic Learning for Mean Field Games and Mean Field Control in Continuous Spaces
by: Fouque, Jean-Pierre, et al.
Published: (2025)

Convergence Analysis of Real-time Recurrent Learning (RTRL) for a class of Recurrent Neural Networks
by: Lam, Samuel Chun-Hei, et al.
Published: (2025)

Convergence of SGD for Training Neural Networks with Sliced Wasserstein Losses
by: Tanguy, Eloi
Published: (2023)

Scaling Effects and Uncertainty Quantification in Neural Actor Critic Algorithms
by: Georgoudios, Nikos, et al.
Published: (2026)

Finite-Time Complexity of Online Primal-Dual Natural Actor-Critic Algorithm for Constrained Markov Decision Processes
by: Zeng, Sihan, et al.
Published: (2021)

Convergence rates for the Adam optimizer
by: Dereich, Steffen, et al.
Published: (2024)

Convergence Error Analysis of Reflected Gradient Langevin Dynamics for Globally Optimizing Non-Convex Constrained Problems
by: Sato, Kanji, et al.
Published: (2022)

Neural Actor-Critic Methods for Hamilton-Jacobi-Bellman PDEs: Asymptotic Analysis and Numerical Studies
by: Cohen, Samuel N., et al.
Published: (2025)

A Generalization Result for Convergence in Learning-to-Optimize
by: Sucker, Michael, et al.
Published: (2024)

Kernel Limit for a Class of Recurrent Neural Networks Trained on Ergodic Data Sequences
by: Lam, Samuel Chun-Hei, et al.
Published: (2023)

Controlling the Flow: Stability and Convergence for Stochastic Gradient Descent with Decaying Regularization
by: Kassing, Sebastian, et al.
Published: (2025)

Prelimit Coupling and Steady-State Convergence of Constant-stepsize Nonsmooth Contractive SA
by: Zhang, Yixuan, et al.
Published: (2024)

Wasserstein Convergence of Score-based Generative Models under Semiconvexity and Discontinuous Gradients
by: Bruno, Stefano, et al.
Published: (2025)

Rates of Convergence in the Central Limit Theorem for Markov Chains, with an Application to TD Learning
by: Srikant, R.
Published: (2024)

Online Learning and Optimization for Queues with Unknown Demand Curve and Service Distribution
by: Chen, Xinyun, et al.
Published: (2023)

Designing Algorithms for Entropic Optimal Transport from an Optimisation Perspective
by: Srinivasan, Vishwak, et al.
Published: (2025)

Improved Approximation Algorithms for Orthogonally Constrained Problems Using Semidefinite Optimization
by: Cory-Wright, Ryan, et al.
Published: (2025)

Algorithmic Stability of Stochastic Gradient Descent with Momentum under Heavy-Tailed Noise
by: Dang, Thanh, et al.
Published: (2025)

Polygonal Unadjusted Langevin Algorithms: Creating stable and efficient adaptive algorithms for neural networks
by: Lim, Dong-Young, et al.
Published: (2021)

Online Resource Allocation with Average Budget Constraints
by: Ao, Ruicheng, et al.
Published: (2024)

Neural Wasserstein Gradient Flows for Maximum Mean Discrepancies with Riesz Kernels
by: Altekrüger, Fabian, et al.
Published: (2023)

Convergence rate of Tsallis entropic regularized optimal transport
by: Suguro, Takeshi, et al.
Published: (2023)

The Performance Of The Unadjusted Langevin Algorithm Without Smoothness Assumptions
by: Johnston, Tim, et al.
Published: (2025)

A Communication-Efficient Decentralized Actor-Critic Algorithm
by: Ren, Xiaoxing, et al.
Published: (2025)

Convergence of linear programming hierarchies for Gibbs states of spin systems
by: Fawzi, Hamza, et al.
Published: (2025)

Convergence of coordinate ascent variational inference for log-concave measures via optimal transport
by: Arnese, Manuel, et al.
Published: (2024)

Natural Policy Gradient and Actor Critic Methods for Constrained Multi-Task Reinforcement Learning
by: Zeng, Sihan, et al.
Published: (2024)

Neural Hilbert Ladders: Multi-Layer Neural Networks in Function Space
by: Chen, Zhengdao
Published: (2023)

Stochastic Inverse Problem: stability, regularization and Wasserstein gradient flow
by: Li, Qin, et al.
Published: (2024)

Statistical Inference for Linear Functionals of Online SGD in High-dimensional Linear Regression
by: Agrawalla, Bhavya, et al.
Published: (2023)

Neural Brownian Motion
by: Qi, Qian
Published: (2025)

Beyond Non-Degeneracy: Revisiting Certainty Equivalent Heuristic for Online Linear Programming
by: Chen, Yilun, et al.
Published: (2025)

Convergence Analysis of the PAGE Stochastic Algorithm for Weakly Convex Finite-Sum Optimization
by: Condat, Laurent, et al.
Published: (2025)

Convergence Analysis of Newton's Method for Neural Networks in the Overparameterized Limit
by: Riedl, Konstantin, et al.
Published: (2026)

Efficient Risk-sensitive Planning via Entropic Risk Measures
by: Marthe, Alexandre, et al.
Published: (2025)

Robust $Q$-learning Algorithm for Markov Decision Processes under Wasserstein Uncertainty
by: Neufeld, Ariel, et al.
Published: (2022)

Convergence rate of random scan Coordinate Ascent Variational Inference under log-concavity
by: Lavenant, Hugo, et al.
Published: (2024)

Convergence of Distributed Adaptive Optimization with Local Updates
by: Cheng, Ziheng, et al.
Published: (2024)

Efficient Online Learning in Interacting Particle Systems
by: Sharrock, Louis, et al.
Published: (2026)

Dynamical Measure Transport and Neural PDE Solvers for Sampling
by: Sun, Jingtong, et al.
Published: (2024)