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 jhui.github.io
"Deep learning - Computation & optimization."
| | matthewmcateer.me
The Math Behind ML (the important stuff) - matthewmcateer.me
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| | Important mathematical prerequisites for getting into Machine Learning, Deep Learning, or any of the other space
| | iclr-blogposts.github.io
How to compute Hessian-vector products? | ICLR Blogposts 2024
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| | The product between the Hessian of a function and a vector, the Hessian-vector product (HVP), is a fundamental quantity to study the variation of a function. It is ubiquitous in traditional optimization and machine learning. However, the computation of HVPs is often considered prohibitive in the context of deep learning, driving practitioners to use proxy quantities to evaluate the loss geometry. Standard automatic differentiation theory predicts that the computational complexity of an HVP is of the same order of magnitude as the complexity of computing a gradient. The goal of this blog post is to provide a practical counterpart to this theoretical result, showing that modern automatic differentiation frameworks, JAX and PyTorch, allow for efficient computat...
| | aria42.com
Numerical Optimization: Understanding L-BFGS - aria42
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| | Numerical optimization is at the core of much of machine learning. In this post, we derive the L-BFGS algorithm, commonly used in batch machine learning applications.
| | swethatanamala.github.io
NLP - Summary of Sequence to Sequence with Neural Networks ยท Swetha's Blog
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| The authors developed a straightforward application of the Long Short-Term Memory (LSTM) architecture which can solve English to French translation.