conftrace_

gradient descent

1144 papers

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Also known as

GD

Co-occurring keywords

neural network (6616) neural network optimization (1293) convex optimization (1321) non-convex optimization (547) convergence rate (607) stochastic optimization (1060) convergence analysis (395) stochastic gradient descent (1091) nonconvex optimization (316) implicit bia (107)

Papers

Unified Gradient-Based Machine Unlearning with Remain Geometry Enhancement NIPS 2024
Stable Minima Cannot Overfit in Univariate ReLU Networks: Generalization by Large Step Sizes NIPS 2024
Tight Convergence Rate Bounds for Optimization Under Power Law Spectral Conditions JMLR 2024
Large Stepsize Gradient Descent for Non-Homogeneous Two-Layer Networks: Margin Improvement and Fast Optimization NIPS 2024
Training Integrable Parameterizations of Deep Neural Networks in the Infinite-Width Limit JMLR 2024
Nesterov acceleration despite very noisy gradients NIPS 2024
Memory-Efficient LLM Training with Online Subspace Descent NIPS 2024
QBB: Quantization with Binary Bases for LLMs NIPS 2024
Guaranteed Nonconvex Factorization Approach for Tensor Train Recovery JMLR 2024
The Feature Speed Formula: a flexible approach to scale hyper-parameters of deep neural networks NIPS 2024
The Implicit Bias of Gradient Descent toward Collaboration between Layers: A Dynamic Analysis of Multilayer Perceptions NIPS 2024
On the Stability and Generalization of Meta-Learning NIPS 2024
Mechanics of Next Token Prediction with Self-Attention AISTATS 2024
Implicit Regularization in Deep Tucker Factorization: Low-Rankness via Structured Sparsity AISTATS 2024
Gradient Reweighting: Towards Imbalanced Class-Incremental Learning CVPR 2024
The Implicit Bias of Gradient Descent on Separable Multiclass Data NIPS 2024
SDEs for Minimax Optimization AISTATS 2024
How Two-Layer Neural Networks Learn, One (Giant) Step at a Time JMLR 2024
An Efficient Stochastic Algorithm for Decentralized Nonconvex-Strongly-Concave Minimax Optimization AISTATS 2024
Parameter-Agnostic Optimization under Relaxed Smoothness AISTATS 2024
On Convergence in Wasserstein Distance and f-divergence Minimization Problems AISTATS 2024
Open Problem: Anytime Convergence Rate of Gradient Descent COLT 2024
The Closeness of In-Context Learning and Weight Shifting for Softmax Regression NIPS 2024
Evolution and learning in differentiable robots RSS 2024
GRAWA: Gradient-based Weighted Averaging for Distributed Training of Deep Learning Models AISTATS 2024