stochastic gradient descent

Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks AISTATS 2024 Linear Convergence of Black-Box Variational Inference: Should We Stick the Landing? AISTATS 2024 Log Barriers for Safe Black-box Optimization with Application to Safe Reinforcement Learning JMLR 2024 Mean-Field Analysis for Learning Subspace-Sparse Polynomials with Gaussian Input NeurIPS 2024 Nearly Tight Black-Box Auditing of Differentially Private Machine Learning NeurIPS 2024 Near-Optimal Streaming Heavy-Tailed Statistical Estimation with Clipped SGD NeurIPS 2024 Neural network learns low-dimensional polynomials with SGD near the information-theoretic limit NeurIPS 2024 Non-asymptotic Analysis of Biased Adaptive Stochastic Approximation NeurIPS 2024 Nonparametric Instrumental Variable Regression through Stochastic Approximate Gradients NeurIPS 2024 On Convergence of Adam for Stochastic Optimization under Relaxed Assumptions NeurIPS 2024 On Estimating the Gradient of the Expected Information Gain in Bayesian Experimental Design AAAI 2024 Online Bilevel Optimization: Regret Analysis of Online Alternating Gradient Methods AISTATS 2024 Online Sensitivity Optimization in Differentially Private Learning AAAI 2024 On the Complexity of Learning Sparse Functions with Statistical and Gradient Queries NeurIPS 2024 On the Convergence of Loss and Uncertainty-based Active Learning Algorithms NeurIPS 2024 On the Effect of Batch Size in Byzantine-Robust Distributed Learning ICLR 2024 On the Generalization of Stochastic Gradient Descent with Momentum JMLR 2024 On the Hyperparameters in Stochastic Gradient Descent with Momentum JMLR 2024 On the Role of Server Momentum in Federated Learning AAAI 2024 Open problem: Convergence of single-timescale mean-field Langevin descent-ascent for two-player zero-sum games COLT 2024 OptEx: Expediting First-Order Optimization with Approximately Parallelized Iterations NeurIPS 2024 Overparametrized Multi-layer Neural Networks: Uniform Concentration of Neural Tangent Kernel and Convergence of Stochastic Gradient Descent JMLR 2024 Parameter-Agnostic Optimization under Relaxed Smoothness AISTATS 2024 Parameter Symmetry and Noise Equilibrium of Stochastic Gradient Descent NeurIPS 2024 Performative Control for Linear Dynamical Systems NeurIPS 2024