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"

50 / 313 papers shown

Title
Deep multi-task mining Calabi-Yau four-folds Harold Erbin Riccardo Finotello Robin Schneider M. Tamaazousti 35 17 0 04 Aug 2021
Simple, Fast, and Flexible Framework for Matrix Completion with Infinite Width Neural Networks Adityanarayanan Radhakrishnan George Stefanakis M. Belkin Caroline Uhler 30 25 0 31 Jul 2021
The loss landscape of deep linear neural networks: a second-order analysis E. M. Achour Franccois Malgouyres Sébastien Gerchinovitz ODL 24 9 0 28 Jul 2021
Reasoning-Modulated Representations Petar Velivcković Matko Bovsnjak Thomas Kipf Alexander Lerchner R. Hadsell Razvan Pascanu Charles Blundell OCL OOD SSL 13 15 0 19 Jul 2021
Improved Learning Rates for Stochastic Optimization: Two Theoretical Viewpoints Shaojie Li Yong Liu 23 13 0 19 Jul 2021
A Theory of PAC Learnability of Partial Concept Classes N. Alon Steve Hanneke R. Holzman Shay Moran 25 50 0 18 Jul 2021
A Field Guide to Federated Optimization Jianyu Wang Zachary B. Charles Zheng Xu Gauri Joshi H. B. McMahan ... Mi Zhang Tong Zhang Chunxiang Zheng Chen Zhu Wennan Zhu FedML 187 412 0 14 Jul 2021
Random Neural Networks in the Infinite Width Limit as Gaussian Processes Boris Hanin BDL 32 43 0 04 Jul 2021
A Mechanism for Producing Aligned Latent Spaces with Autoencoders Saachi Jain Adityanarayanan Radhakrishnan Caroline Uhler 21 9 0 29 Jun 2021
Jitter: Random Jittering Loss Function Zhicheng Cai Chenglei Peng S. Du 21 3 0 25 Jun 2021
Training Graph Neural Networks with 1000 Layers Guohao Li Matthias Muller Guohao Li V. Koltun GNN AI4CE 51 235 0 14 Jun 2021
Pre-Trained Models: Past, Present and Future Xu Han Zhengyan Zhang Ning Ding Yuxian Gu Xiao Liu ... Jie Tang Ji-Rong Wen Jinhui Yuan Wayne Xin Zhao Jun Zhu AIFin MQ AI4MH 40 815 0 14 Jun 2021
The Limitations of Large Width in Neural Networks: A Deep Gaussian Process Perspective Geoff Pleiss John P. Cunningham 28 24 0 11 Jun 2021
Neural Symbolic Regression that Scales Luca Biggio Tommaso Bendinelli Alexander Neitz Aurelien Lucchi Giambattista Parascandolo 54 170 0 11 Jun 2021
Double Descent and Other Interpolation Phenomena in GANs Lorenzo Luzi Yehuda Dar Richard Baraniuk 26 5 0 07 Jun 2021
On Memorization in Probabilistic Deep Generative Models G. V. D. Burg Christopher K. I. Williams TDI 25 59 0 06 Jun 2021
Towards an Understanding of Benign Overfitting in Neural Networks Zhu Li Zhi-Hua Zhou Arthur Gretton MLT 33 35 0 06 Jun 2021
Fundamental tradeoffs between memorization and robustness in random features and neural tangent regimes Elvis Dohmatob 25 9 0 04 Jun 2021
A Universal Law of Robustness via Isoperimetry Sébastien Bubeck Mark Sellke 13 213 0 26 May 2021
Relative stability toward diffeomorphisms indicates performance in deep nets Leonardo Petrini Alessandro Favero Mario Geiger M. Wyart OOD 38 15 0 06 May 2021
A Geometric Analysis of Neural Collapse with Unconstrained Features Zhihui Zhu Tianyu Ding Jinxin Zhou Xiao Li Chong You Jeremias Sulam Qing Qu 27 194 0 06 May 2021
AdaBoost and robust one-bit compressed sensing Geoffrey Chinot Felix Kuchelmeister Matthias Löffler Sara van de Geer 35 5 0 05 May 2021
Deep limits and cut-off phenomena for neural networks B. Avelin A. Karlsson AI4CE 38 2 0 21 Apr 2021
Fundamental Challenges in Deep Learning for Stiff Contact Dynamics Mihir Parmar Mathew Halm Michael Posa 29 36 0 29 Mar 2021
Embracing the Disharmony in Medical Imaging: A Simple and Effective Framework for Domain Adaptation Rongguang Wang Pratik Chaudhari Christos Davatzikos OOD 42 49 0 23 Mar 2021
The Shape of Learning Curves: a Review T. Viering Marco Loog 18 122 0 19 Mar 2021
Lost in Pruning: The Effects of Pruning Neural Networks beyond Test Accuracy Lucas Liebenwein Cenk Baykal Brandon Carter David K Gifford Daniela Rus AAML 40 71 0 04 Mar 2021
Slow-Growing Trees Philippe Goulet Coulombe 31 1 0 02 Mar 2021
Provable Super-Convergence with a Large Cyclical Learning Rate Samet Oymak 33 12 0 22 Feb 2021
Learning curves of generic features maps for realistic datasets with a teacher-student model Bruno Loureiro Cédric Gerbelot Hugo Cui Sebastian Goldt Florent Krzakala M. Mézard Lenka Zdeborová 35 135 0 16 Feb 2021
Low Curvature Activations Reduce Overfitting in Adversarial Training Vasu Singla Sahil Singla David Jacobs S. Feizi AAML 32 45 0 15 Feb 2021
Learning Curve Theory Marcus Hutter 140 59 0 08 Feb 2021
Exploring Deep Neural Networks via Layer-Peeled Model: Minority Collapse in Imbalanced Training Cong Fang Hangfeng He Qi Long Weijie J. Su FAtt 130 167 0 29 Jan 2021
Analysis of the Scalability of a Deep-Learning Network for Steganography "Into the Wild" Hugo Ruiz Marc Chaumont Mehdi Yedroudj A. Amara Frédéric Comby Gérard Subsol 29 9 0 29 Dec 2020
Applying Deutsch's concept of good explanations to artificial intelligence and neuroscience -- an initial exploration Daniel C. Elton 23 4 0 16 Dec 2020
Provable Benefits of Overparameterization in Model Compression: From Double Descent to Pruning Neural Networks Xiangyu Chang Yingcong Li Samet Oymak Christos Thrampoulidis 35 50 0 16 Dec 2020
A case for new neural network smoothness constraints Mihaela Rosca T. Weber Arthur Gretton S. Mohamed AAML 33 48 0 14 Dec 2020
Understanding Double Descent Requires a Fine-Grained Bias-Variance Decomposition Ben Adlam Jeffrey Pennington UD 39 93 0 04 Nov 2020
A Bayesian Perspective on Training Speed and Model Selection Clare Lyle Lisa Schut Binxin Ru Y. Gal Mark van der Wilk 44 24 0 27 Oct 2020
Are wider nets better given the same number of parameters? A. Golubeva Behnam Neyshabur Guy Gur-Ari 27 44 0 27 Oct 2020
Memorizing without overfitting: Bias, variance, and interpolation in over-parameterized models J. Rocks Pankaj Mehta 18 41 0 26 Oct 2020
Precise High-Dimensional Asymptotics for Quantifying Heterogeneous Transfers Fan Yang Hongyang R. Zhang Sen Wu Christopher Ré Weijie J. Su 58 10 0 22 Oct 2020
Precise Statistical Analysis of Classification Accuracies for Adversarial Training Adel Javanmard Mahdi Soltanolkotabi AAML 28 62 0 21 Oct 2020
For self-supervised learning, Rationality implies generalization, provably Yamini Bansal Gal Kaplun Boaz Barak OOD SSL 58 22 0 16 Oct 2020
Regularizing Neural Networks via Adversarial Model Perturbation Yaowei Zheng Richong Zhang Yongyi Mao AAML 30 95 0 10 Oct 2020
Effective Regularization Through Loss-Function Metalearning Santiago Gonzalez Risto Miikkulainen 29 5 0 02 Oct 2020
Small Data, Big Decisions: Model Selection in the Small-Data Regime J. Bornschein Francesco Visin Simon Osindero 15 36 0 26 Sep 2020
Towards a Mathematical Understanding of Neural Network-Based Machine Learning: what we know and what we don't E. Weinan Chao Ma Stephan Wojtowytsch Lei Wu AI4CE 22 133 0 22 Sep 2020
Efficient Quantum State Sample Tomography with Basis-dependent Neural-networks Alistair W. R. Smith Johnnie Gray M. S. Kim 11 28 0 16 Sep 2020
Minimum discrepancy principle strategy for choosing $k$ in $k$ -NN regression Yaroslav Averyanov Alain Celisse 18 0 0 20 Aug 2020