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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"

38 / 938 papers shown

Title
Generalization in Reinforcement Learning with Selective Noise Injection and Information BottleneckNeural Information Processing Systems (NeurIPS), 2019 Maximilian Igl K. Ciosek Yingzhen Li Sebastian Tschiatschek Cheng Zhang Sam Devlin Katja Hofmann OffRL 175 187 0 28 Oct 2019
Capacity, Bandwidth, and Compositionality in Emergent Language LearningAdaptive Agents and Multi-Agent Systems (AAMAS), 2019 Cinjon Resnick Abhinav Gupta Jakob N. Foerster Andrew M. Dai Dong Wang 223 52 0 24 Oct 2019
Causal bootstrapping Max A. Little Reham Badawy CML 129 21 0 21 Oct 2019
The Implicit Regularization of Ordinary Least Squares EnsemblesInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019 Daniel LeJeune Hamid Javadi Richard G. Baraniuk 200 46 0 10 Oct 2019
Backpropagation Algorithms and Reservoir Computing in Recurrent Neural Networks for the Forecasting of Complex Spatiotemporal DynamicsNeural Networks (NN), 2019 Pantelis R. Vlachas Jaideep Pathak Brian R. Hunt T. Sapsis M. Girvan Edward Ott Petros Koumoutsakos AI4TS 249 439 0 09 Oct 2019
A Function Space View of Bounded Norm Infinite Width ReLU Nets: The Multivariate CaseInternational Conference on Learning Representations (ICLR), 2019 Greg Ongie Rebecca Willett Daniel Soudry Nathan Srebro 183 169 0 03 Oct 2019
Predicting materials properties without crystal structure: Deep representation learning from stoichiometryNature Communications (Nat Commun), 2019 Rhys E. A. Goodall A. Lee 189 293 0 01 Oct 2019
Overparameterized Neural Networks Implement Associative MemoryProceedings of the National Academy of Sciences of the United States of America (PNAS), 2019 Adityanarayanan Radhakrishnan M. Belkin Caroline Uhler BDL 199 76 0 26 Sep 2019
Finite Depth and Width Corrections to the Neural Tangent KernelInternational Conference on Learning Representations (ICLR), 2019 Boris Hanin Mihai Nica MDE 185 162 0 13 Sep 2019
Learning Algebraic Models of Quantum EntanglementQuantum Information Processing (QIP), 2019 Hamza Jaffali Luke Oeding 150 10 0 27 Aug 2019
Implicit Deep LearningSIAM Journal on Mathematics of Data Science (SIMODS), 2019 L. Ghaoui Fangda Gu Bertrand Travacca Armin Askari Alicia Y. Tsai AI4CE 331 198 0 17 Aug 2019
The generalization error of random features regression: Precise asymptotics and double descent curveCommunications on Pure and Applied Mathematics (CPAM), 2019 Song Mei Andrea Montanari 461 669 0 14 Aug 2019
Behaviour Suite for Reinforcement LearningInternational Conference on Learning Representations (ICLR), 2019 Ian Osband Yotam Doron Matteo Hessel John Aslanides Eren Sezener ... Satinder Singh Benjamin Van Roy R. Sutton David Silver H. V. Hasselt OffRL 221 196 0 09 Aug 2019
On the Existence of Simpler Machine Learning ModelsConference on Fairness, Accountability and Transparency (FAccT), 2019 Lesia Semenova Cynthia Rudin Ronald E. Parr 313 107 0 05 Aug 2019
Minimizers of the Empirical Risk and Risk MonotonicityNeural Information Processing Systems (NeurIPS), 2019 Marco Loog T. Viering A. Mey 190 30 0 11 Jul 2019
Benign Overfitting in Linear RegressionProceedings of the National Academy of Sciences of the United States of America (PNAS), 2019 Peter L. Bartlett Philip M. Long Gábor Lugosi Alexander Tsigler MLT 369 847 0 26 Jun 2019
Finding the Needle in the Haystack with Convolutions: on the benefits of architectural biasNeural Information Processing Systems (NeurIPS), 2019 Stéphane dÁscoli Levent Sagun Joan Bruna Giulio Biroli 150 37 0 16 Jun 2019
Does Learning Require Memorization? A Short Tale about a Long TailSymposium on the Theory of Computing (STOC), 2019 Vitaly Feldman TDI 519 575 0 12 Jun 2019
The Generalization-Stability Tradeoff In Neural Network PruningNeural Information Processing Systems (NeurIPS), 2019 Brian Bartoldson Ari S. Morcos Adrian Barbu G. Erlebacher 273 84 0 09 Jun 2019
Understanding overfitting peaks in generalization error: Analytical risk curves for $l_2$ and $l_1$ penalized interpolation P. Mitra 176 50 0 09 Jun 2019
Implicit Rugosity Regularization via Data Augmentation Daniel LeJeune Randall Balestriero Hamid Javadi Richard G. Baraniuk 178 4 0 28 May 2019
Quantifying the generalization error in deep learning in terms of data distribution and neural network smoothnessNeural Networks (NN), 2019 Pengzhan Jin Lu Lu Yifa Tang George Karniadakis 302 64 0 27 May 2019
Linearized two-layers neural networks in high dimensionAnnals of Statistics (Ann. Stat.), 2019 Behrooz Ghorbani Song Mei Theodor Misiakiewicz Andrea Montanari MLT 222 255 0 27 Apr 2019
The Impact of Neural Network Overparameterization on Gradient Confusion and Stochastic Gradient Descent Karthik A. Sankararaman Soham De Zheng Xu Wenjie Huang Tom Goldstein ODL 232 114 0 15 Apr 2019
A Selective Overview of Deep Learning Jianqing Fan Cong Ma Yiqiao Zhong BDL VLM 359 143 0 10 Apr 2019
Regularized Learning for Domain Adaptation under Label Shifts Kamyar Azizzadenesheli Anqi Liu Fanny Yang Anima Anandkumar 118 217 0 22 Mar 2019
Surprises in High-Dimensional Ridgeless Least Squares InterpolationAnnals of Statistics (Ann. Stat.), 2019 Trevor Hastie Andrea Montanari Saharon Rosset Robert Tibshirani 799 809 0 19 Mar 2019
Two models of double descent for weak featuresSIAM Journal on Mathematics of Data Science (SIMODS), 2019 M. Belkin Daniel J. Hsu Ji Xu 304 392 0 18 Mar 2019
Sparse evolutionary Deep Learning with over one million artificial neurons on commodity hardware Shiwei Liu Decebal Constantin Mocanu A. R. Ramapuram Matavalam Yulong Pei Mykola Pechenizkiy BDL 260 94 0 26 Jan 2019
Training Neural Networks as Learning Data-adaptive Kernels: Provable Representation and Approximation Benefits Xialiang Dou Tengyuan Liang MLT 228 42 0 21 Jan 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 Matthieu Wyart 264 203 0 06 Jan 2019
On the Benefit of Width for Neural Networks: Disappearance of Bad Basins Dawei Li Tian Ding Tian Ding 435 41 0 28 Dec 2018
A Modern Take on the Bias-Variance Tradeoff in Neural Networks Brady Neal Sarthak Mittal A. Baratin Vinayak Tantia Matthew Scicluna Damien Scieur Alexia Jolicoeur-Martineau 191 178 0 19 Oct 2018
Small ReLU networks are powerful memorizers: a tight analysis of memorization capacity Chulhee Yun S. Sra Ali Jadbabaie 314 122 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 337 229 0 02 Oct 2018
Data augmentation instead of explicit regularization Alex Hernández-García Peter König 221 155 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 210 96 0 28 May 2018
High-dimensional dynamics of generalization error in neural networks Madhu S. Advani Andrew M. Saxe AI4CE 249 495 0 10 Oct 2017