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

Evolution and learning in differentiable robots RSS 2024
Dropout Regularization Versus l2-Penalization in the Linear Model JMLR 2024
GGD: Grafting Gradient Descent JMLR 2024
Open Problem: Anytime Convergence Rate of Gradient Descent COLT 2024
An Efficient Stochastic Algorithm for Decentralized Nonconvex-Strongly-Concave Minimax Optimization AISTATS 2024
Pruning is Optimal for Learning Sparse Features in High-Dimensions COLT 2024
Convergence of Gradient Descent with Small Initialization for Unregularized Matrix Completion COLT 2024
Large Stepsize Gradient Descent for Logistic Loss: Non-Monotonicity of the Loss Improves Optimization Efficiency COLT 2024
Private Stochastic Convex Optimization with Heavy Tails: Near-Optimality from Simple Reductions NIPS 2024
Training Integrable Parameterizations of Deep Neural Networks in the Infinite-Width Limit JMLR 2024
On Convergence in Wasserstein Distance and f-divergence Minimization Problems AISTATS 2024
On Partial Optimal Transport: Revising the Infeasibility of Sinkhorn and Efficient Gradient Methods AAAI 2024
In-Context Learning with Representations: Contextual Generalization of Trained Transformers NIPS 2024
Neural Redshift: Random Networks are not Random Functions CVPR 2024
Generalization and Stability of Interpolating Neural Networks with Minimal Width JMLR 2024
Sharpness-Aware Minimization and the Edge of Stability JMLR 2024
Langevin Unlearning: A New Perspective of Noisy Gradient Descent for Machine Unlearning NIPS 2024
Initializing Services in Interactive ML Systems for Diverse Users NIPS 2024
One-Layer Transformer Provably Learns One-Nearest Neighbor In Context NIPS 2024
Differentially Private Optimization with Sparse Gradients NIPS 2024
Globally Convergent Variational Inference NIPS 2024
Unraveling the Gradient Descent Dynamics of Transformers NIPS 2024
GRAWA: Gradient-based Weighted Averaging for Distributed Training of Deep Learning Models AISTATS 2024
Changing the Training Data Distribution to Reduce Simplicity Bias Improves In-distribution Generalization NIPS 2024
In-Context Learning of a Linear Transformer Block: Benefits of the MLP Component and One-Step GD Initialization NIPS 2024