An Information-Theoretic Framework for Supervised Learning

1 March 2022

Papers citing "An Information-Theoretic Framework for Supervised Learning"

7 / 7 papers shown

Title
Information-Theoretic Foundations for Neural Scaling Laws Hong Jun Jeon Benjamin Van Roy 32 1 0 28 Jun 2024
Stochastic Thermodynamics of Learning Parametric Probabilistic Models S. Parsi 47 0 0 04 Oct 2023
Continual Learning as Computationally Constrained Reinforcement Learning Saurabh Kumar Henrik Marklund Anand Srinivasa Rao Yifan Zhu Hong Jun Jeon Yueyang Liu Benjamin Van Roy CLL 27 22 0 10 Jul 2023
An Information-Theoretic Analysis of Compute-Optimal Neural Scaling Laws Hong Jun Jeon Benjamin Van Roy 16 0 0 02 Dec 2022
Is Stochastic Gradient Descent Near Optimal? Yifan Zhu Hong Jun Jeon Benjamin Van Roy 25 2 0 18 Sep 2022
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 308 2,892 0 15 Sep 2016
Norm-Based Capacity Control in Neural Networks Behnam Neyshabur Ryota Tomioka Nathan Srebro 127 577 0 27 Feb 2015