The No Free Lunch Theorem, Kolmogorov Complexity, and the Role of
Inductive Biases in Machine Learning

The No Free Lunch Theorem, Kolmogorov Complexity, and the Role of Inductive Biases in Machine Learning

11 April 2023

Papers citing "The No Free Lunch Theorem, Kolmogorov Complexity, and the Role of Inductive Biases in Machine Learning"

11 / 11 papers shown

Title
A Mathematical Philosophy of Explanations in Mechanistic Interpretability -- The Strange Science Part I.i Kola Ayonrinde Louis Jaburi MILM 84 1 0 01 May 2025
A Complexity-Based Theory of Compositionality Eric Elmoznino Thomas Jiralerspong Yoshua Bengio Guillaume Lajoie CoGe 56 4 0 18 Oct 2024
In-context learning and Occam's razor Eric Elmoznino Tom Marty Tejas Kasetty Léo Gagnon Sarthak Mittal Mahan Fathi Dhanya Sridhar Guillaume Lajoie 32 1 0 17 Oct 2024
Neural Redshift: Random Networks are not Random Functions Damien Teney A. Nicolicioiu Valentin Hartmann Ehsan Abbasnejad 92 18 0 04 Mar 2024
Fine-Tuned Language Models Generate Stable Inorganic Materials as Text Nate Gruver Anuroop Sriram Andrea Madotto A. Wilson C. L. Zitnick Zachary W. Ulissi 25 55 0 06 Feb 2024
Bayesian Model Selection, the Marginal Likelihood, and Generalization Sanae Lotfi Pavel Izmailov Gregory W. Benton Micah Goldblum A. Wilson UQCV BDL 52 56 0 23 Feb 2022
Patches Are All You Need? Asher Trockman J. Zico Kolter ViT 216 402 0 24 Jan 2022
Stochastic Training is Not Necessary for Generalization Jonas Geiping Micah Goldblum Phillip E. Pope Michael Moeller Tom Goldstein 81 72 0 29 Sep 2021
A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups Marc Finzi Max Welling A. Wilson 71 185 0 19 Apr 2021
A Theoretical Analysis of the Repetition Problem in Text Generation Z. Fu Wai Lam Anthony Man-Cho So Bei Shi 69 90 0 29 Dec 2020
Pac-Bayesian Supervised Classification: The Thermodynamics of Statistical Learning O. Catoni 137 453 0 03 Dec 2007