Evaluation of Neural Architectures Trained with Square Loss vs Cross-Entropy in Classification Tasks

12 June 2020

Papers citing "Evaluation of Neural Architectures Trained with Square Loss vs Cross-Entropy in Classification Tasks"

45 / 45 papers shown

Title
Super-fast rates of convergence for Neural Networks Classifiers under the Hard Margin Condition Nathanael Tepakbong Ding-Xuan Zhou Xiang Zhou 33 0 0 13 May 2025
Continuous Visual Autoregressive Generation via Score Maximization Chenze Shao Fandong Meng Jie Zhou DiffM 26 0 0 12 May 2025
The Silent Majority: Demystifying Memorization Effect in the Presence of Spurious Correlations Chenyu You Haocheng Dai Yifei Min Jasjeet Sekhon S. Joshi James S. Duncan 60 2 0 01 Jan 2025
Does SGD really happen in tiny subspaces? Minhak Song Kwangjun Ahn Chulhee Yun 66 4 1 25 May 2024
Towards Certification of Uncertainty Calibration under Adversarial Attacks Cornelius Emde Francesco Pinto Thomas Lukasiewicz Philip H. S. Torr Adel Bibi AAML 42 0 0 22 May 2024
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
A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks Vignesh Kothapalli Tom Tirer Joan Bruna 34 10 0 04 Jul 2023
Dual Focal Loss for Calibration Linwei Tao Minjing Dong Chang Xu UQCV 37 26 0 23 May 2023
Fairness Uncertainty Quantification: How certain are you that the model is fair? Abhishek Roy P. Mohapatra 14 5 0 27 Apr 2023
Automatic Gradient Descent: Deep Learning without Hyperparameters Jeremy Bernstein Chris Mingard Kevin Huang Navid Azizan Yisong Yue ODL 16 17 0 11 Apr 2023
General Loss Functions Lead to (Approximate) Interpolation in High Dimensions Kuo-Wei Lai Vidya Muthukumar 18 5 0 13 Mar 2023
Generalizing and Decoupling Neural Collapse via Hyperspherical Uniformity Gap Weiyang Liu L. Yu Adrian Weller Bernhard Schölkopf 32 17 0 11 Mar 2023
Calibrating a Deep Neural Network with Its Predecessors Linwei Tao Minjing Dong Daochang Liu Changming Sun Chang Xu BDL UQCV 6 5 0 13 Feb 2023
Cut your Losses with Squentropy Like Hui M. Belkin S. Wright UQCV 13 8 0 08 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
Supervision Complexity and its Role in Knowledge Distillation Hrayr Harutyunyan A. S. Rawat A. Menon Seungyeon Kim Surinder Kumar 22 12 0 28 Jan 2023
Annealing Double-Head: An Architecture for Online Calibration of Deep Neural Networks Erdong Guo D. Draper Maria de Iorio 35 0 0 27 Dec 2022
Principled and Efficient Transfer Learning of Deep Models via Neural Collapse Xiao Li Sheng Liu Jin-li Zhou Xin Lu C. Fernandez‐Granda Zhihui Zhu Q. Qu AAML 23 18 0 23 Dec 2022
Perturbation Analysis of Neural Collapse Tom Tirer Haoxiang Huang Jonathan Niles-Weed AAML 30 23 0 29 Oct 2022
The Fisher-Rao Loss for Learning under Label Noise Henrique K. Miyamoto Fábio C. C. Meneghetti Sueli I. R. Costa NoLa 18 5 0 28 Oct 2022
Towards Understanding GD with Hard and Conjugate Pseudo-labels for Test-Time Adaptation Jun-Kun Wang Andre Wibisono 29 7 0 18 Oct 2022
Are All Losses Created Equal: A Neural Collapse Perspective Jinxin Zhou Chong You Xiao Li Kangning Liu Sheng Liu Qing Qu Zhihui Zhu 30 58 0 04 Oct 2022
Behind the Scenes of Gradient Descent: A Trajectory Analysis via Basis Function Decomposition Jianhao Ma Li-Zhen Guo S. Fattahi 38 4 0 01 Oct 2022
Scale-invariant Bayesian Neural Networks with Connectivity Tangent Kernel Sungyub Kim Si-hun Park Kyungsu Kim Eunho Yang BDL 26 4 0 30 Sep 2022
Blessing of Nonconvexity in Deep Linear Models: Depth Flattens the Optimization Landscape Around the True Solution Jianhao Ma S. Fattahi 40 5 0 15 Jul 2022
Making Look-Ahead Active Learning Strategies Feasible with Neural Tangent Kernels Mohamad Amin Mohamadi Wonho Bae Danica J. Sutherland 28 20 0 25 Jun 2022
Neural Collapse: A Review on Modelling Principles and Generalization Vignesh Kothapalli 21 71 0 08 Jun 2022
Standalone Neural ODEs with Sensitivity Analysis Rym Jaroudi Lukáš Malý Gabriel Eilertsen B. Johansson Jonas Unger George Baravdish 21 0 0 27 May 2022
Investigating Generalization by Controlling Normalized Margin Alexander R. Farhang Jeremy Bernstein Kushal Tirumala Yang Liu Yisong Yue 25 6 0 08 May 2022
The Effects of Regularization and Data Augmentation are Class Dependent Randall Balestriero Léon Bottou Yann LeCun 28 94 0 07 Apr 2022
Generalization Through The Lens Of Leave-One-Out Error Gregor Bachmann Thomas Hofmann Aurélien Lucchi 44 7 0 07 Mar 2022
On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features Jinxin Zhou Xiao Li Tian Ding Chong You Qing Qu Zhihui Zhu 22 97 0 02 Mar 2022
On the Regularization of Autoencoders Harald Steck Dario Garcia-Garcia SSL AI4CE 27 4 0 21 Oct 2021
slimTrain -- A Stochastic Approximation Method for Training Separable Deep Neural Networks Elizabeth Newman Julianne Chung Matthias Chung Lars Ruthotto 39 6 0 28 Sep 2021
A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning Yehuda Dar Vidya Muthukumar Richard G. Baraniuk 29 71 0 06 Sep 2021
Memorization in Deep Neural Networks: Does the Loss Function matter? Deep Patel P. Sastry TDI 13 8 0 21 Jul 2021
Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation Haoxiang Wang Han Zhao Bo-wen Li 29 88 0 16 Jun 2021
RATT: Leveraging Unlabeled Data to Guarantee Generalization Saurabh Garg Sivaraman Balakrishnan J. Zico Kolter Zachary Chase Lipton 28 29 0 01 May 2021
Understanding and Mitigating Accuracy Disparity in Regression Jianfeng Chi Yuan Tian Geoffrey J. Gordon Han Zhao 16 25 0 24 Feb 2021
Modeling Dynamic User Interests: A Neural Matrix Factorization Approach Paramveer S. Dhillon Sinan Aral AI4TS 17 19 0 12 Feb 2021
Estimating informativeness of samples with Smooth Unique Information Hrayr Harutyunyan Alessandro Achille Giovanni Paolini Orchid Majumder Avinash Ravichandran Rahul Bhotika Stefano Soatto 16 24 0 17 Jan 2021
Gradient Starvation: A Learning Proclivity in Neural Networks Mohammad Pezeshki Sekouba Kaba Yoshua Bengio Aaron Courville Doina Precup Guillaume Lajoie MLT 45 257 0 18 Nov 2020
Classification vs regression in overparameterized regimes: Does the loss function matter? Vidya Muthukumar Adhyyan Narang Vignesh Subramanian M. Belkin Daniel J. Hsu A. Sahai 36 148 0 16 May 2020
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 297 6,956 0 20 Apr 2018
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,136 0 06 Jun 2015