Bias-variance decomposition of overparameterized regression with random linear features

10 March 2022

Papers citing "Bias-variance decomposition of overparameterized regression with random linear features"

7 / 7 papers shown

Title
Correlating and Predicting Human Evaluations of Language Models from Natural Language Processing Benchmarks Rylan Schaeffer Punit Singh Koura Binh Tang R. Subramanian Aaditya K. Singh ... Vedanuj Goswami Sergey Edunov Dieuwke Hupkes Sanmi Koyejo Sharan Narang ALM 146 1 0 24 Feb 2025
Towards an Improved Understanding and Utilization of Maximum Manifold Capacity Representations Rylan Schaeffer Victor Lecomte Dhruv Pai Andres Carranza Berivan Isik ... Yann LeCun SueYeon Chung Andrey Gromov Ravid Shwartz-Ziv Sanmi Koyejo 103 8 0 13 Jun 2024
It's an Alignment, Not a Trade-off: Revisiting Bias and Variance in Deep Models Lin Chen Michal Lukasik Wittawat Jitkrittum Chong You Sanjiv Kumar 77 1 0 13 Oct 2023
Double Descent Demystified: Identifying, Interpreting & Ablating the Sources of a Deep Learning Puzzle Rylan Schaeffer Mikail Khona Zachary Robertson Akhilan Boopathy Kateryna Pistunova J. Rocks Ila Rani Fiete Oluwasanmi Koyejo 146 35 0 24 Mar 2023
Error mitigation of entangled states using brainbox quantum autoencoders Joséphine Pazem M. Ansari 70 4 0 02 Mar 2023
Learning curves for deep structured Gaussian feature models Jacob A. Zavatone-Veth Cengiz Pehlevan MLT 90 11 0 01 Mar 2023
Contrasting random and learned features in deep Bayesian linear regression Jacob A. Zavatone-Veth William L. Tong Cengiz Pehlevan BDL MLT 135 28 0 01 Mar 2022