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global convergence

111 papers

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policy gradient (518) non-convex optimization (546) gradient descent (1143) stochastic gradient descent (1088) neural network (6616) neural network optimization (1293) convergence rate (606) convex optimization (1320) sample complexity (1158) expectation maximization (254)

Papers

Langevin Multiplicative Weights Update with Applications in Polynomial Portfolio Management AAAI 2025
Global Convergence of Adjoint-Optimized Neural PDEs JMLR 2025
An Enhanced Levenberg--Marquardt Method via Gram Reduction AAAI 2025
Toward Global Convergence of Gradient EM for Over-Paramterized Gaussian Mixture Models NIPS 2024
Convergence of Gradient Descent with Small Initialization for Unregularized Matrix Completion COLT 2024
Small steps no more: Global convergence of stochastic gradient bandits for arbitrary learning rates NIPS 2024
Global Convergence in Training Large-Scale Transformers NIPS 2024
Adaptive Quasi-Newton and Anderson Acceleration Framework with Explicit Global (Accelerated) Convergence Rates AISTATS 2024
PPO-Clip Attains Global Optimality: Towards Deeper Understandings of Clipping AAAI 2024
Non-asymptotic Global Convergence Analysis of BFGS with the Armijo-Wolfe Line Search NIPS 2024
FastSurvival: Hidden Computational Blessings in Training Cox Proportional Hazards Models NIPS 2024
Last-Iterate Global Convergence of Policy Gradients for Constrained Reinforcement Learning NIPS 2024
Regret Analysis of Policy Gradient Algorithm for Infinite Horizon Average Reward Markov Decision Processes AAAI 2024
Matryoshka Policy Gradient for Entropy-Regularized RL: Convergence and Global Optimality JMLR 2024
Globally Q-linear Gauss-Newton Method for Overparameterized Non-convex Matrix Sensing NIPS 2024
On the Global Convergence of Fitted Q-Iteration with Two-layer Neural Network Parametrization ICML 2023
Stochastic Gradient Succeeds for Bandits ICML 2023
Global Convergence of Sub-gradient Method for Robust Matrix Recovery: Small Initialization, Noisy Measurements, and Over-parameterization JMLR 2023
Policy Gradient in Robust MDPs with Global Convergence Guarantee ICML 2023
Stochastic Policy Gradient Methods: Improved Sample Complexity for Fisher-non-degenerate Policies ICML 2023
On the Global Convergence of Risk-Averse Policy Gradient Methods with Expected Conditional Risk Measures ICML 2023
Coordinate Ascent for Off-Policy RL with Global Convergence Guarantees AISTATS 2023
Global Convergence Analysis of Local SGD for Two-layer Neural Network without Overparameterization NIPS 2023
Global Convergence of Over-parameterized Deep Equilibrium Models AISTATS 2023
Gradient Descent Finds the Global Optima of Two-Layer Physics-Informed Neural Networks ICML 2023