A Modern Take on the Bias-Variance Tradeoff in Neural Networks

19 October 2018

Papers citing "A Modern Take on the Bias-Variance Tradeoff in Neural Networks"

29 / 29 papers shown

Title
Gabor-Enhanced Physics-Informed Neural Networks for Fast Simulations of Acoustic Wavefields Mohammad Mahdi Abedi David Pardo Tariq Alkhalifah 49 1 0 24 Feb 2025
Understanding Model Ensemble in Transferable Adversarial Attack Wei Yao Zeliang Zhang Huayi Tang Yong Liu 33 2 0 09 Oct 2024
Breaking Neural Network Scaling Laws with Modularity Akhilan Boopathy Sunshine Jiang William Yue Jaedong Hwang Abhiram Iyer Ila Fiete OOD 39 2 0 09 Sep 2024
Rethinking Semi-Supervised Imbalanced Node Classification from Bias-Variance Decomposition Divin Yan Gengchen Wei Chen Yang Shengzhong Zhang Zengfeng Huang AI4CE 38 11 0 28 Oct 2023
Training-Free Neural Active Learning with Initialization-Robustness Guarantees Apivich Hemachandra Zhongxiang Dai Jasraj Singh See-Kiong Ng K. H. Low AAML 30 6 0 07 Jun 2023
Lower bounds for the trade-off between bias and mean absolute deviation A. Derumigny Johannes Schmidt-Hieber 27 0 0 21 Mar 2023
Pathologies of Predictive Diversity in Deep Ensembles Taiga Abe E. Kelly Buchanan Geoff Pleiss John P. Cunningham UQCV 38 13 0 01 Feb 2023
Task Discovery: Finding the Tasks that Neural Networks Generalize on Andrei Atanov Andrei Filatov Teresa Yeo Ajay Sohmshetty Amir Zamir OOD 40 10 0 01 Dec 2022
Understanding the double descent curve in Machine Learning Luis Sa-Couto J. M. Ramos Miguel Almeida Andreas Wichert 16 1 0 18 Nov 2022
Packed-Ensembles for Efficient Uncertainty Estimation Olivier Laurent Adrien Lafage Enzo Tartaglione Geoffrey Daniel Jean-Marc Martinez Andrei Bursuc Gianni Franchi OODD 44 32 0 17 Oct 2022
The Dynamic of Consensus in Deep Networks and the Identification of Noisy Labels Daniel Shwartz Uri Stern D. Weinshall NoLa 33 2 0 02 Oct 2022
Deep Double Descent via Smooth Interpolation Matteo Gamba Erik Englesson Marten Bjorkman Hossein Azizpour 56 10 0 21 Sep 2022
Membership Inference Attacks and Generalization: A Causal Perspective Teodora Baluta Shiqi Shen S. Hitarth Shruti Tople Prateek Saxena OOD MIACV 40 18 0 18 Sep 2022
The BUTTER Zone: An Empirical Study of Training Dynamics in Fully Connected Neural Networks Charles Edison Tripp J. Perr-Sauer L. Hayne M. Lunacek Jamil Gafur AI4CE 21 0 0 25 Jul 2022
Regularization-wise double descent: Why it occurs and how to eliminate it Fatih Yilmaz Reinhard Heckel 25 11 0 03 Jun 2022
Understanding the bias-variance tradeoff of Bregman divergences Ben Adlam Neha Gupta Zelda E. Mariet Jamie Smith UQCV UD 15 6 0 08 Feb 2022
An Analysis on Ensemble Learning optimized Medical Image Classification with Deep Convolutional Neural Networks Dominik Muller Iñaki Soto Rey Frank Kramer 16 56 0 27 Jan 2022
More layers! End-to-end regression and uncertainty on tabular data with deep learning Ivan Bondarenko OOD LMTD UQCV 17 4 0 07 Dec 2021
Multi-scale Feature Learning Dynamics: Insights for Double Descent Mohammad Pezeshki Amartya Mitra Yoshua Bengio Guillaume Lajoie 58 25 0 06 Dec 2021
From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness Lingxiao Zhao Wei Jin L. Akoglu Neil Shah GNN 24 160 0 07 Oct 2021
Understanding Double Descent Requires a Fine-Grained Bias-Variance Decomposition Ben Adlam Jeffrey Pennington UD 29 92 0 04 Nov 2020
Multiple Descent: Design Your Own Generalization Curve Lin Chen Yifei Min M. Belkin Amin Karbasi DRL 18 61 0 03 Aug 2020
A Survey of End-to-End Driving: Architectures and Training Methods Ardi Tampuu Maksym Semikin Naveed Muhammad D. Fishman Tambet Matiisen 3DV 18 228 0 13 Mar 2020
Double Trouble in Double Descent : Bias and Variance(s) in the Lazy Regime Stéphane dÁscoli Maria Refinetti Giulio Biroli Florent Krzakala 93 152 0 02 Mar 2020
Generalisation error in learning with random features and the hidden manifold model Federica Gerace Bruno Loureiro Florent Krzakala M. Mézard Lenka Zdeborová 25 165 0 21 Feb 2020
Implicit Regularization of Random Feature Models Arthur Jacot Berfin Simsek Francesco Spadaro Clément Hongler Franck Gabriel 18 82 0 19 Feb 2020
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 39 194 0 06 Jan 2019
Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural Networks Lechao Xiao Yasaman Bahri Jascha Narain Sohl-Dickstein S. Schoenholz Jeffrey Pennington 220 348 0 14 Jun 2018
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 281 2,888 0 15 Sep 2016