learning rate
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- North America > United States > Maryland (0.04)
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- North America > United States > Iowa > Story County > Ames (0.04)
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Temperature Balancing, Layer-wise Weight Analysis, and Neural Network Training Yefan Zhou
However, such a global learning rate schedule does not take into account the structural characteristics of neural networks (NNs).
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- Europe > Switzerland > Zürich > Zürich (0.14)
- Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.04)
- North America > United States > California (0.04)
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- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (1.00)
- Information Technology > Artificial Intelligence > Representation & Reasoning > Uncertainty > Bayesian Inference (0.67)
- Information Technology > Artificial Intelligence > Machine Learning > Learning Graphical Models > Directed Networks > Bayesian Learning (0.67)
- Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning > Gradient Descent (0.46)
SHOT: Suppressing the Hessian along the Optimization Trajectory for Gradient-Based Meta-Learning
To validate the effectiveness of SHOT, we conduct empirical tests on standard few-shot learning tasks and qualitatively analyze its dynamics.
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- North America > United States > California (0.04)
- Europe > Germany > North Rhine-Westphalia > Upper Bavaria > Munich (0.04)
- Asia > South Korea > Seoul > Seoul (0.04)
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Stability-penalty-adaptive follow-the-regularized-leader: Sparsity, game-dependency, and best-of-both-worlds
Adaptivity to the difficulties of a problem is a key property in sequential decision-making problems to broaden the applicability of algorithms.
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- Asia > Japan > Honshū > Kansai > Kyoto Prefecture > Kyoto (0.04)
- Asia > Japan > Honshū > Kantō > Tokyo Metropolis Prefecture > Tokyo (0.04)
- Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.04)
Technology: Information Technology > Artificial Intelligence > Machine Learning > Reinforcement Learning (0.34)
Stability-penalty-adaptive follow-the-regularized-leader: Sparsity, game-dependency, and best-of-both-worlds
Adaptivity to the difficulties of a problem is a key property in sequential decision-making problems to broaden the applicability of algorithms.
Country:
- Asia > Japan > Honshū > Kansai > Kyoto Prefecture > Kyoto (0.04)
- Asia > Japan > Honshū > Kantō > Tokyo Metropolis Prefecture > Tokyo (0.04)
- Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.04)
Technology: Information Technology > Artificial Intelligence > Machine Learning > Reinforcement Learning (0.34)
Sharpness-Aware Minimization Leads to Low-Rank Features
Sharpness-aware minimization (SAM) is a recently proposed method that minimizes the sharpness of the training loss of a neural network.
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