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

Newton Losses: Using Curvature Information for Learning with Differentiable Algorithms NIPS 2024
The Implicit Bias of Gradient Descent toward Collaboration between Layers: A Dynamic Analysis of Multilayer Perceptions NIPS 2024
Learning Low-Rank Tensor Cores with Probabilistic ℓ0-Regularized Rank Selection for Model Compression IJCAI 2024
QLABGrad: A Hyperparameter-Free and Convergence-Guaranteed Scheme for Deep Learning AAAI 2024
On the Stability and Generalization of Meta-Learning NIPS 2024
In-context Learning and Gradient Descent Revisited NAACL 2024
Mechanics of Next Token Prediction with Self-Attention AISTATS 2024
MetaDiff: Meta-Learning with Conditional Diffusion for Few-Shot Learning AAAI 2024
Implicit Regularization in Deep Tucker Factorization: Low-Rankness via Structured Sparsity AISTATS 2024
Analyzing & Reducing the Need for Learning Rate Warmup in GPT Training NIPS 2024
On the Power of Small-size Graph Neural Networks for Linear Programming NIPS 2024
Unraveling the Gradient Descent Dynamics of Transformers NIPS 2024
The Implicit Bias of Gradient Descent on Separable Multiclass Data NIPS 2024
Conflict-Alleviated Gradient Descent for Adaptive Object Detection IJCAI 2024
DP-AdamBC: Your DP-Adam Is Actually DP-SGD (Unless You Apply Bias Correction) AAAI 2024
In-Context Learning of a Linear Transformer Block: Benefits of the MLP Component and One-Step GD Initialization NIPS 2024
EG-NAS: Neural Architecture Search with Fast Evolutionary Exploration AAAI 2024
Robust and Faster Zeroth-Order Minimax Optimization: Complexity and Applications NIPS 2024
Parameter-Agnostic Optimization under Relaxed Smoothness AISTATS 2024
Ink Dot-Oriented Differentiable Optimization for Neural Image Halftoning CVPR 2024
The Closeness of In-Context Learning and Weight Shifting for Softmax Regression NIPS 2024
Initializing Services in Interactive ML Systems for Diverse Users NIPS 2024
Guaranteed Nonconvex Factorization Approach for Tensor Train Recovery JMLR 2024
FedSOL: Stabilized Orthogonal Learning with Proximal Restrictions in Federated Learning CVPR 2024
Tight Convergence Rate Bounds for Optimization Under Power Law Spectral Conditions JMLR 2024