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 / 273 papers shown

Title
What, Indeed, is an Achievable Provable Guarantee for Learning-Enabled Safety Critical Systems Saddek Bensalem Chih-Hong Cheng Wei Huang Xiaowei Huang Changshun Wu Xingyu Zhao AAML 24 6 0 20 Jul 2023
The Interpolating Information Criterion for Overparameterized Models Liam Hodgkinson Christopher van der Heide Roberto Salomone Fred Roosta Michael W. Mahoney 20 7 0 15 Jul 2023
Quantifying lottery tickets under label noise: accuracy, calibration, and complexity V. Arora Daniele Irto Sebastian Goldt G. Sanguinetti 36 2 0 21 Jun 2023
Progressive Class-Wise Attention (PCA) Approach for Diagnosing Skin Lesions Asim Naveed Syed S. Naqvi Tariq Mahmood Khan Imran Razzak 31 1 0 11 Jun 2023
Gibbs-Based Information Criteria and the Over-Parameterized Regime Haobo Chen Yuheng Bu Greg Wornell 27 1 0 08 Jun 2023
Maximally Machine-Learnable Portfolios Philippe Goulet Coulombe Maximilian Göbel 21 3 0 08 Jun 2023
Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capability Jianing Zhu Hengzhuang Li Jiangchao Yao Tongliang Liu Jianliang Xu Bo Han OODD 40 12 0 06 Jun 2023
Unraveling Projection Heads in Contrastive Learning: Insights from Expansion and Shrinkage Yu Gui Cong Ma Yiqiao Zhong 22 6 0 06 Jun 2023
Generalized equivalences between subsampling and ridge regularization Pratik V. Patil Jin-Hong Du 29 5 0 29 May 2023
Optimization's Neglected Normative Commitments Benjamin Laufer T. Gilbert Helen Nissenbaum OffRL 21 4 0 27 May 2023
Double Descent of Discrepancy: A Task-, Data-, and Model-Agnostic Phenomenon Yi-Xiao Luo Bin Dong 26 0 0 25 May 2023
When are ensembles really effective? Ryan Theisen Hyunsuk Kim Yaoqing Yang Liam Hodgkinson Michael W. Mahoney FedML UQCV 35 15 0 21 May 2023
Towards understanding neural collapse in supervised contrastive learning with the information bottleneck method Siwei Wang S. Palmer 24 2 0 19 May 2023
Target-Side Augmentation for Document-Level Machine Translation Guangsheng Bao Zhiyang Teng Yue Zhang 26 10 0 08 May 2023
Is deep learning a useful tool for the pure mathematician? G. Williamson FedML 21 13 0 25 Apr 2023
Learning Trajectories are Generalization Indicators Jingwen Fu Zhizheng Zhang Dacheng Yin Yan Lu Nanning Zheng AI4CE 28 3 0 25 Apr 2023
Prediction-Oriented Bayesian Active Learning Freddie Bickford-Smith Andreas Kirsch Sebastian Farquhar Y. Gal Adam Foster Tom Rainforth 29 29 0 17 Apr 2023
Analysis of Interpolating Regression Models and the Double Descent Phenomenon T. McKelvey 4 0 0 17 Apr 2023
Mathematical Challenges in Deep Learning V. Nia Guojun Zhang I. Kobyzev Michael R. Metel Xinlin Li ... S. Hemati M. Asgharian Linglong Kong Wulong Liu Boxing Chen AI4CE VLM 37 1 0 24 Mar 2023
Online Learning for the Random Feature Model in the Student-Teacher Framework Roman Worschech B. Rosenow 41 0 0 24 Mar 2023
Lower bounds for the trade-off between bias and mean absolute deviation A. Derumigny Johannes Schmidt-Hieber 27 0 0 21 Mar 2023
Memorization Capacity of Neural Networks with Conditional Computation Erdem Koyuncu 30 4 0 20 Mar 2023
Deep Learning Weight Pruning with RMT-SVD: Increasing Accuracy and Reducing Overfitting Yitzchak Shmalo Jonathan Jenkins Oleksii Krupchytskyi 22 3 0 15 Mar 2023
Tradeoff of generalization error in unsupervised learning Gilhan Kim Ho-Jun Lee Junghyo Jo Yongjoo Baek 13 0 0 10 Mar 2023
DSD $^2$ : Can We Dodge Sparse Double Descent and Compress the Neural Network Worry-Free? Victor Quétu Enzo Tartaglione 26 7 0 02 Mar 2023
Penalising the biases in norm regularisation enforces sparsity Etienne Boursier Nicolas Flammarion 34 14 0 02 Mar 2023
Approximately optimal domain adaptation with Fisher's Linear Discriminant Hayden S. Helm Ashwin De Silva Joshua T. Vogelstein Carey E. Priebe Weiwei Yang 29 2 0 27 Feb 2023
Can we avoid Double Descent in Deep Neural Networks? Victor Quétu Enzo Tartaglione AI4CE 20 3 0 26 Feb 2023
Precise Asymptotic Analysis of Deep Random Feature Models David Bosch Ashkan Panahi B. Hassibi 35 19 0 13 Feb 2023
Better Diffusion Models Further Improve Adversarial Training Zekai Wang Tianyu Pang Chao Du Min-Bin Lin Weiwei Liu Shuicheng Yan DiffM 24 208 0 09 Feb 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
Implicit Regularization Leads to Benign Overfitting for Sparse Linear Regression Mo Zhou Rong Ge 27 2 0 01 Feb 2023
MOSAIC, acomparison framework for machine learning models Mattéo Papin Yann Beaujeault-Taudiere F. Magniette VLM 16 0 0 30 Jan 2023
On the Lipschitz Constant of Deep Networks and Double Descent Matteo Gamba Hossein Azizpour Marten Bjorkman 25 7 0 28 Jan 2023
A Simple Algorithm For Scaling Up Kernel Methods Tengyu Xu Bryan T. Kelly Semyon Malamud 11 0 0 26 Jan 2023
A Stability Analysis of Fine-Tuning a Pre-Trained Model Z. Fu Anthony Man-Cho So Nigel Collier 23 3 0 24 Jan 2023
Towards NeuroAI: Introducing Neuronal Diversity into Artificial Neural Networks Fenglei Fan Yingxin Li Hanchuan Peng T. Zeng Fei-Yue Wang 22 5 0 23 Jan 2023
Strong inductive biases provably prevent harmless interpolation Michael Aerni Marco Milanta Konstantin Donhauser Fanny Yang 30 9 0 18 Jan 2023
WLD-Reg: A Data-dependent Within-layer Diversity Regularizer Firas Laakom Jenni Raitoharju Alexandros Iosifidis M. Gabbouj AI4CE 26 7 0 03 Jan 2023
Problem-Dependent Power of Quantum Neural Networks on Multi-Class Classification Yuxuan Du Yibo Yang Dacheng Tao Min-hsiu Hsieh 36 22 0 29 Dec 2022
Gradient flow in the gaussian covariate model: exact solution of learning curves and multiple descent structures Antione Bodin N. Macris 34 4 0 13 Dec 2022
$Tight bounds for maximum $\ell_1$-margin classifiers$ Tight bounds for maximum $\ell_1$ -margin classifiers Stefan Stojanovic Konstantin Donhauser Fanny Yang 40 0 0 07 Dec 2022
High Dimensional Binary Classification under Label Shift: Phase Transition and Regularization Jiahui Cheng Minshuo Chen Hao Liu Tuo Zhao Wenjing Liao 34 0 0 01 Dec 2022
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
Why Neural Networks Work Sayan Mukherjee Bernardo A. Huberman 11 2 0 26 Nov 2022
The Vanishing Decision Boundary Complexity and the Strong First Component Hengshuai Yao UQCV 30 0 0 25 Nov 2022
A Survey of Learning Curves with Bad Behavior: or How More Data Need Not Lead to Better Performance Marco Loog T. Viering 21 1 0 25 Nov 2022
Understanding the double descent curve in Machine Learning Luis Sa-Couto J. M. Ramos Miguel Almeida Andreas Wichert 27 1 0 18 Nov 2022
Emergence of Concepts in DNNs? Tim Räz 19 0 0 11 Nov 2022
Do highly over-parameterized neural networks generalize since bad solutions are rare? Julius Martinetz T. Martinetz 22 1 0 07 Nov 2022