Reconciling modern machine learning practice and the bias-variance trade-off

28 December 2018

Papers citing "Reconciling modern machine learning practice and the bias-variance trade-off"

23 / 273 papers shown

Title
Machine Learning from a Continuous Viewpoint E. Weinan Chao Ma Lei Wu 23 102 0 30 Dec 2019
Exact expressions for double descent and implicit regularization via surrogate random design Michal Derezinski Feynman T. Liang Michael W. Mahoney 16 77 0 10 Dec 2019
In Defense of Uniform Convergence: Generalization via derandomization with an application to interpolating predictors Jeffrey Negrea Gintare Karolina Dziugaite Daniel M. Roy AI4CE 29 64 0 09 Dec 2019
A Model of Double Descent for High-dimensional Binary Linear Classification Zeyu Deng A. Kammoun Christos Thrampoulidis 34 143 0 13 Nov 2019
Rate-Regularization and Generalization in VAEs Alican Bozkurt Babak Esmaeili Jean-Baptiste Tristan Dana H. Brooks Jennifer G. Dy Jan Willem van de Meent DRL 25 7 0 11 Nov 2019
Capacity, Bandwidth, and Compositionality in Emergent Language Learning Cinjon Resnick Abhinav Gupta Jakob N. Foerster Andrew M. Dai Kyunghyun Cho 18 51 0 24 Oct 2019
Predicting materials properties without crystal structure: Deep representation learning from stoichiometry Rhys E. A. Goodall A. Lee 11 253 0 01 Oct 2019
Overparameterized Neural Networks Implement Associative Memory Adityanarayanan Radhakrishnan M. Belkin Caroline Uhler BDL 27 71 0 26 Sep 2019
Finite Depth and Width Corrections to the Neural Tangent Kernel Boris Hanin Mihai Nica MDE 22 150 0 13 Sep 2019
Implicit Deep Learning L. Ghaoui Fangda Gu Bertrand Travacca Armin Askari Alicia Y. Tsai AI4CE 34 176 0 17 Aug 2019
The generalization error of random features regression: Precise asymptotics and double descent curve Song Mei Andrea Montanari 47 626 0 14 Aug 2019
Behaviour Suite for Reinforcement Learning Ian Osband Yotam Doron Matteo Hessel John Aslanides Eren Sezener ... Satinder Singh Benjamin Van Roy R. Sutton David Silver H. V. Hasselt OffRL 13 178 0 09 Aug 2019
On the Existence of Simpler Machine Learning Models Lesia Semenova Cynthia Rudin Ronald E. Parr 26 85 0 05 Aug 2019
Does Learning Require Memorization? A Short Tale about a Long Tail Vitaly Feldman TDI 21 481 0 12 Jun 2019
Linearized two-layers neural networks in high dimension Behrooz Ghorbani Song Mei Theodor Misiakiewicz Andrea Montanari MLT 18 241 0 27 Apr 2019
A Selective Overview of Deep Learning Jianqing Fan Cong Ma Yiqiao Zhong BDL VLM 28 136 0 10 Apr 2019
Two models of double descent for weak features M. Belkin Daniel J. Hsu Ji Xu 17 375 0 18 Mar 2019
Scaling description of generalization with number of parameters in deep learning Mario Geiger Arthur Jacot S. Spigler Franck Gabriel Levent Sagun Stéphane dÁscoli Giulio Biroli Clément Hongler M. Wyart 44 194 0 06 Jan 2019
Small ReLU networks are powerful memorizers: a tight analysis of memorization capacity Chulhee Yun S. Sra Ali Jadbabaie 18 117 0 17 Oct 2018
Implicit Self-Regularization in Deep Neural Networks: Evidence from Random Matrix Theory and Implications for Learning Charles H. Martin Michael W. Mahoney AI4CE 30 190 0 02 Oct 2018
Data augmentation instead of explicit regularization Alex Hernández-García Peter König 30 141 0 11 Jun 2018
Optimal ridge penalty for real-world high-dimensional data can be zero or negative due to the implicit ridge regularization D. Kobak Jonathan Lomond Benoit Sanchez 24 89 0 28 May 2018
High-dimensional dynamics of generalization error in neural networks Madhu S. Advani Andrew M. Saxe AI4CE 47 464 0 10 Oct 2017