The no-free-lunch theorems of supervised learning

9 February 2022

Papers citing "The no-free-lunch theorems of supervised learning"

9 / 9 papers shown

Title
Generating Skyline Datasets for Data Science Models Mengying Wang Hanchao Ma Yiyang Bian Yangxin Fan Yinghui Wu 39 0 0 16 Feb 2025
A General Theory for Compositional Generalization Jingwen Fu Zhizheng Zhang Yan Lu Nanning Zheng AI4CE CoGe 26 2 0 20 May 2024
Statistical learning theory and Occam's razor: The argument from empirical risk minimization T. Sterkenburg CML 11 3 0 21 Dec 2023
Transgressing the boundaries: towards a rigorous understanding of deep learning and its (non-)robustness C. Hartmann Lorenz Richter AAML 21 2 0 05 Jul 2023
Relax, it doesn't matter how you get there: A new self-supervised approach for multi-timescale behavior analysis Mehdi Azabou Michael J. Mendelson Nauman Ahad Maks Sorokin S. Thakoor Carolina Urzay Eva L. Dyer 20 4 0 15 Mar 2023
ML Interpretability: Simple Isn't Easy Tim Räz MILM 15 14 0 24 Nov 2022
A Link between Coding Theory and Cross-Validation with Applications T. Pahikkala P. Movahedi I. Perez Havu Miikonen I. Jambor A. Airola László Major 11 0 0 22 Mar 2021
Absolutely No Free Lunches! G. Belot 9 10 0 10 May 2020
Norm-Based Capacity Control in Neural Networks Behnam Neyshabur Ryota Tomioka Nathan Srebro 119 577 0 27 Feb 2015