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 / 266 papers shown

Title
A dynamic view of the double descent Vivek Shripad Borkar 58 0 0 03 May 2025
Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing Jiarui Xie Y. Zhao 49 0 0 30 Apr 2025
Sobolev norm inconsistency of kernel interpolation Yunfei Yang 34 0 0 29 Apr 2025
Grokking in the Wild: Data Augmentation for Real-World Multi-Hop Reasoning with Transformers Roman Abramov Felix Steinbauer Gjergji Kasneci 138 0 0 29 Apr 2025
The Double Descent Behavior in Two Layer Neural Network for Binary Classification Chathurika S Abeykoon A. Beknazaryan Hailin Sang 51 1 0 27 Apr 2025
auto-fpt: Automating Free Probability Theory Calculations for Machine Learning Theory Arjun Subramonian Elvis Dohmatob 24 0 0 14 Apr 2025
Gradient Descent Robustly Learns the Intrinsic Dimension of Data in Training Convolutional Neural Networks Chenyang Zhang Peifeng Gao Difan Zou Yuan Cao OOD MLT 59 0 0 11 Apr 2025
Analyzing the Role of Permutation Invariance in Linear Mode Connectivity Keyao Zhan Puheng Li Lei Wu MoMe 79 0 0 13 Mar 2025
On the Relationship Between Double Descent of CNNs and Shape/Texture Bias Under Learning Process Shun Iwase Shuya Takahashi Nakamasa Inoue Rio Yokota Ryo Nakamura Hirokatsu Kataoka 74 0 0 04 Mar 2025
From Small to Large Language Models: Revisiting the Federalist Papers So Won Jeong Veronika Rockova 37 0 0 25 Feb 2025
Early Stopping Against Label Noise Without Validation Data Suqin Yuan Lei Feng Tongliang Liu NoLa 96 14 0 11 Feb 2025
The late-stage training dynamics of (stochastic) subgradient descent on homogeneous neural networks Sholom Schechtman Nicolas Schreuder 147 0 0 08 Feb 2025
How more data can hurt: Instability and regularization in next-generation reservoir computing Yuanzhao Zhang Edmilson Roque dos Santos Sean P. Cornelius 77 2 0 28 Jan 2025
Functional Risk Minimization Ferran Alet Clement Gehring Tomás Lozano-Pérez Kenji Kawaguchi Joshua B. Tenenbaum Leslie Pack Kaelbling OffRL 60 0 0 31 Dec 2024
Analysis of High-dimensional Gaussian Labeled-unlabeled Mixture Model via Message-passing Algorithm Xiaosi Gu Tomoyuki Obuchi 69 0 0 29 Nov 2024
Puzzle: Distillation-Based NAS for Inference-Optimized LLMs Akhiad Bercovich Tomer Ronen Talor Abramovich Nir Ailon Nave Assaf ... Ido Shahaf Oren Tropp Omer Ullman Argov Ran Zilberstein Ran El-Yaniv 77 1 0 28 Nov 2024
Theoretical characterisation of the Gauss-Newton conditioning in Neural Networks Jim Zhao Sidak Pal Singh Aurélien Lucchi AI4CE 43 0 0 04 Nov 2024
High-dimensional Analysis of Knowledge Distillation: Weak-to-Strong Generalization and Scaling Laws M. E. Ildiz Halil Alperen Gozeten Ege Onur Taga Marco Mondelli Samet Oymak 54 2 0 24 Oct 2024
Understanding Model Ensemble in Transferable Adversarial Attack Wei Yao Zeliang Zhang Huayi Tang Yong Liu 33 2 0 09 Oct 2024
Extended convexity and smoothness and their applications in deep learning Binchuan Qi Wei Gong Li Li 61 0 0 08 Oct 2024
Investigating the Impact of Model Complexity in Large Language Models Jing Luo Huiyuan Wang Weiran Huang 34 0 0 01 Oct 2024
Zero-shot forecasting of chaotic systems Yuanzhao Zhang William Gilpin AI4TS 37 4 0 24 Sep 2024
Monomial Matrix Group Equivariant Neural Functional Networks Hoang V. Tran Thieu N. Vo Tho H. Tran An T. Nguyen Tan M. Nguyen 54 5 0 18 Sep 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
Theoretical Insights into Overparameterized Models in Multi-Task and Replay-Based Continual Learning Mohammadamin Banayeeanzade Mahdi Soltanolkotabi Mohammad Rostami CLL LRM 95 1 0 29 Aug 2024
Optimal Kernel Quantile Learning with Random Features Caixing Wang Xingdong Feng 42 0 0 24 Aug 2024
Can all variations within the unified mask-based beamformer framework achieve identical peak extraction performance? Atsuo Hiroe Katsutoshi Itoyama Kazuhiro Nakadai 35 0 0 22 Jul 2024
How DNNs break the Curse of Dimensionality: Compositionality and Symmetry Learning Arthur Jacot Seok Hoan Choi Yuxiao Wen AI4CE 91 2 0 08 Jul 2024
Beyond Performance Plateaus: A Comprehensive Study on Scalability in Speech Enhancement Wangyou Zhang Kohei Saijo Jee-weon Jung Chenda Li Shinji Watanabe Yanmin Qian 32 4 0 06 Jun 2024
Data Quality in Edge Machine Learning: A State-of-the-Art Survey M. D. Belgoumri Mohamed Reda Bouadjenek Sunil Aryal Hakim Hacid 41 1 0 01 Jun 2024
A Margin-based Multiclass Generalization Bound via Geometric Complexity Michael Munn Benoit Dherin Javier Gonzalvo UQCV 40 2 0 28 May 2024
Asymptotic theory of in-context learning by linear attention Yue M. Lu Mary I. Letey Jacob A. Zavatone-Veth Anindita Maiti C. Pehlevan 23 10 0 20 May 2024
Beyond Scaling Laws: Understanding Transformer Performance with Associative Memory Xueyan Niu Bo Bai Lei Deng Wei Han 31 6 0 14 May 2024
Faster Convergence of Stochastic Accelerated Gradient Descent under Interpolation Aaron Mishkin Mert Pilanci Mark Schmidt 62 1 0 03 Apr 2024
High-dimensional analysis of ridge regression for non-identically distributed data with a variance profile Jérémie Bigot Issa-Mbenard Dabo Camille Male 29 4 0 29 Mar 2024
Deep Confident Steps to New Pockets: Strategies for Docking Generalization Gabriele Corso Arthur Deng Benjamin Fry Nicholas Polizzi Regina Barzilay Tommi Jaakkola OOD 37 27 0 28 Feb 2024
Predictive Churn with the Set of Good Models J. Watson-Daniels Flavio du Pin Calmon Alexander DÁmour Carol Xuan Long David C. Parkes Berk Ustun 83 7 0 12 Feb 2024
Kernel PCA for Out-of-Distribution Detection Kun Fang Qinghua Tao Kexin Lv M. He Xiaolin Huang Jie-jin Yang OODD 46 2 0 05 Feb 2024
Manipulating Sparse Double Descent Ya Shi Zhang 19 0 0 19 Jan 2024
Weak Correlations as the Underlying Principle for Linearization of Gradient-Based Learning Systems Ori Shem-Ur Yaron Oz 14 0 0 08 Jan 2024
Predictive variational autoencoder for learning robust representations of time-series data Julia Huiming Wang Dexter Tsin Tatiana Engel CML OOD AI4TS 30 2 0 12 Dec 2023
Analysis of the expected $L_2$ error of an over-parametrized deep neural network estimate learned by gradient descent without regularization Selina Drews Michael Kohler 25 2 0 24 Nov 2023
A decorrelation method for general regression adjustment in randomized experiments Fangzhou Su Wenlong Mou Peng Ding Martin J. Wainwright 19 1 0 16 Nov 2023
Unified machine learning tasks and datasets for enhancing renewable energy Arsam Aryandoust Thomas Rigoni Francesco di Stefano Anthony Patt 37 0 0 12 Nov 2023
Changing the Kernel During Training Leads to Double Descent in Kernel Regression Oskar Allerbo 30 0 0 03 Nov 2023
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
Fundamental Limits of Deep Learning-Based Binary Classifiers Trained with Hinge Loss T. Getu Georges Kaddoum M. Bennis 34 1 0 13 Sep 2023
MCPA: Multi-scale Cross Perceptron Attention Network for 2D Medical Image Segmentation Liang Xu Mingxi Chen Yiyu Cheng Pengfei Shao Shuwei Shen Peng Yao Ronald X. Xu ViT 32 0 0 27 Jul 2023
Are Transformers with One Layer Self-Attention Using Low-Rank Weight Matrices Universal Approximators? T. Kajitsuka Issei Sato 29 16 0 26 Jul 2023
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 21 6 0 20 Jul 2023