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Architect Your Landscape Approach (AYLA) for Optimizations in Deep Learning
Architect Your Landscape Approach (AYLA) for Optimizations in Deep Learning
Arxiv
0+阅读 · 4月2日
Spectral-factorized Positive-definite Curvature Learning for NN Training
Arxiv
0+阅读 · 3月28日
Stochastic Gradient Sampling for Enhancing Neural Networks Training
Arxiv
0+阅读 · 3月18日
Accelerating Training with Neuron Interaction and Nowcasting Networks
Arxiv
0+阅读 · 2月27日
Non-convergence to the optimal risk for Adam and stochastic gradient descent optimization in the training of deep neural networks
Arxiv
0+阅读 · 3月3日
Spectral-factorized Positive-definite Curvature Learning for NN Training
Arxiv
0+阅读 · 3月11日
ASGO: Adaptive Structured Gradient Optimization
Arxiv
0+阅读 · 3月26日
Better Embeddings with Coupled Adam
Arxiv
0+阅读 · 2月13日
Better Embeddings with Coupled Adam
Arxiv
0+阅读 · 2月12日
Gradient Multi-Normalization for Stateless and Scalable LLM Training
Arxiv
0+阅读 · 2月10日
SWAN: SGD with Normalization and Whitening Enables Stateless LLM Training
Arxiv
0+阅读 · 2月21日
Understanding Why Adam Outperforms SGD: Gradient Heterogeneity in Transformers
Arxiv
0+阅读 · 1月31日
Non-convergence to global minimizers in data driven supervised deep learning: Adam and stochastic gradient descent optimization provably fail to converge to global minimizers in the training of deep neural networks with ReLU activation
Arxiv
0+阅读 · 2月15日
Spectral-factorized Positive-definite Curvature Learning for NN Training
Arxiv
0+阅读 · 2月10日
SOAP: Improving and Stabilizing Shampoo using Adam
Arxiv
0+阅读 · 1月31日
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