conftrace_
← Keywords

stochastic gradient descent

1088 papers

Explore in graph

Also known as

SGD

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

Spherical Motion Dynamics: Learning Dynamics of Normalized Neural Network using SGD and Weight Decay NIPS 2021
On the distributional properties of adaptive gradients UAI 2021
Towards Tight Communication Lower Bounds for Distributed Optimisation NIPS 2021
Determinantal point processes based on orthogonal polynomials for sampling minibatches in SGD NIPS 2021
An Efficient Algorithm for Deep Stochastic Contextual Bandits AAAI 2021
SGD for Structured Nonconvex Functions: Learning Rates, Minibatching and Interpolation AISTATS 2021
Local Stochastic Gradient Descent Ascent: Convergence Analysis and Communication Efficiency AISTATS 2021
Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence AISTATS 2021
Robustness and scalability under heavy tails, without strong convexity AISTATS 2021
Dynamics of Stochastic Momentum Methods on Large-scale, Quadratic Models NIPS 2021
Benign Overfitting of Constant-Stepsize SGD for Linear Regression COLT 2021
AC-GC: Lossy Activation Compression with Guaranteed Convergence NIPS 2021
Manipulating SGD with Data Ordering Attacks NIPS 2021
Automatic variational inference with cascading flows ICML 2021
Toward Better Generalization Bounds with Locally Elastic Stability ICML 2021
Phase-Wise Parameter Aggregation for Improving SGD Optimization WACV 2021
Exponential Convergence Rates of Classification Errors on Learning with SGD and Random Features AISTATS 2021
Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms NIPS 2021
Closing the Gap: Tighter Analysis of Alternating Stochastic Gradient Methods for Bilevel Problems NIPS 2021
Accelerating Distributed SGD for Linear Regression using Iterative Pre-Conditioning L4DC 2021
vqSGD: Vector Quantized Stochastic Gradient Descent AISTATS 2021
On ADMM in Deep Learning: Convergence and Saturation-Avoidance JMLR 2021
Positive-Negative Momentum: Manipulating Stochastic Gradient Noise to Improve Generalization ICML 2021
Streaming Linear System Identification with Reverse Experience Replay NIPS 2021
Revisiting Model Stitching to Compare Neural Representations NIPS 2021