This is the second post (here’s the first one) about an approach to introducing the derivative to calculus students that is counter to what I’ve seen in textbooks and other traditional treatments of ...
This repository houses useful re-usable formulas and equations for discrete mathematics, linear algebra, and calculus together with an insightful addition of appendices that include proofs, analysis ...
The mathematical foundation of deep learning is the theorem that any continuous function can be approximated within any specified accuracy by using a neural network with certain non-linear activation ...
Curvature-Based Piecewise Linear Approximation Method of GELU Activation Function in Neural Networks
Abstract: Artificial neural networks (ANNs) rely significantly on activation functions for optimal performance. Traditional activation functions such as ReLU and Sigmoid are commonly used. However, ...
We design a new provably efficient algorithm for episodic reinforcement learning with generalized linear function approximation. We analyze the algorithm under a new expressivity assumption that we ...
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