stochastic gradient descent

1088 papers

Explore in graph

Also known as

SGD ASGD SAGA SGM SGDA PSGD SKGD

Co-occurring keywords

non-convex optimization (546) distributed learning (563) neural network optimization (1293) convergence rate (606) convex optimization (1320) neural network (6616) variance reduction (520) stochastic optimization (1060) convergence analysis (394) differential privacy (1010)

Papers

Enhancing DPSGD via Per-Sample Momentum and Low-Pass Filtering AAAI 2026

On the Learning Dynamics of Two-layer Linear Networks with Label Noise SGD AAAI 2026

S-D-RSM: Stochastic Distributed Regularized Splitting Method for Large-Scale Convex Optimization Problems AAAI 2026

A Stylometric and Statistical Pipeline for Urdu AI-Generated Text Classification EACL 2026

An Improved Privacy and Utility Analysis of Differentially Private SGD with Bounded Domain and Smooth Losses AAAI 2026

Investigating the Role of Weight Decay in Enhancing Nonconvex SGD CVPR 2025

Online Quantile Regression JMLR 2025

Towards Stable and Storage-efficient Dataset Distillation: Matching Convexified Trajectory CVPR 2025

Coupling-based Convergence Diagnostic and Stepsize Scheme for Stochastic Gradient Descent AAAI 2025

Explicit and Implicit Graduated Optimization in Deep Neural Networks AAAI 2025

Stabilizing Sharpness-Aware Minimization Through A Simple Renormalization Strategy JMLR 2025

EF21 with Bells & Whistles: Six Algorithmic Extensions of Modern Error Feedback JMLR 2025

Optimal Decentralized Composite Optimization for Strongly Convex Functions JMLR 2025

Upsample or Upweight? Balanced Training on Heavily Imbalanced Datasets NAACL 2025

AdaGK-SGD: Adaptive Global Knowledge Guided Distributed Stochastic Gradient Descent AAAI 2025

Statistical Inference of Random Graphs With a Surrogate Likelihood Function JMLR 2025

Mixing Times and Privacy Analysis for the Projected Langevin Algorithm under a Modulus of Continuity JMLR 2025

Revisiting Gradient Normalization and Clipping for Nonconvex SGD under Heavy-Tailed Noise: Necessity, Sufficiency, and Acceleration JMLR 2025

Approximating Metric Magnitude of Point Sets AAAI 2025

Improved Rates of Differentially Private Nonconvex-Strongly-Concave Minimax Optimization AAAI 2025

Error Analysis Affected by Heavy-Tailed Gradients for Non-Convex Pairwise Stochastic Gradient Descent AAAI 2025

Stability and Generalization of Zeroth-Order Decentralized Stochastic Gradient Descent with Changing Topology AAAI 2025

Characterizing Dynamical Stability of Stochastic Gradient Descent in Overparameterized Learning JMLR 2025

Nonconvex Stochastic Bregman Proximal Gradient Method with Application to Deep Learning JMLR 2025

On the O(sqrt(d)/T^(1/4)) Convergence Rate of RMSProp and Its Momentum Extension Measured by l_1 Norm JMLR 2025