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Cross Entropy versus Label Smoothing: A Neural Collapse Perspective

Cross Entropy versus Label Smoothing: A Neural Collapse Perspective

6 February 2024
Li Guo
George Andriopoulos
Zifan Zhao
Shuyang Ling
Shuyang Ling
Keith Ross
    UQCV
    NoLa
ArXivPDFHTML

Papers citing "Cross Entropy versus Label Smoothing: A Neural Collapse Perspective"

28 / 28 papers shown
Title
Generalized Neural Collapse for a Large Number of Classes
Generalized Neural Collapse for a Large Number of Classes
Jiachen Jiang
Jinxin Zhou
Peng Wang
Qing Qu
Dustin Mixon
Chong You
Zhihui Zhu
AI4CE
53
27
0
09 Oct 2023
Neural Collapse for Unconstrained Feature Model under Cross-entropy Loss
  with Imbalanced Data
Neural Collapse for Unconstrained Feature Model under Cross-entropy Loss with Imbalanced Data
Wanli Hong
Shuyang Ling
47
16
0
18 Sep 2023
Inducing Neural Collapse in Deep Long-tailed Learning
Inducing Neural Collapse in Deep Long-tailed Learning
Xuantong Liu
Jianfeng Zhang
Tianyang Hu
He Cao
Lujia Pan
Yuan Yao
44
31
0
24 Feb 2023
Neural Collapse Inspired Feature-Classifier Alignment for Few-Shot Class
  Incremental Learning
Neural Collapse Inspired Feature-Classifier Alignment for Few-Shot Class Incremental Learning
Yibo Yang
Haobo Yuan
Hefei Ling
Zhouchen Lin
Philip Torr
Dacheng Tao
CLL
67
99
0
06 Feb 2023
Neural Collapse in Deep Linear Networks: From Balanced to Imbalanced
  Data
Neural Collapse in Deep Linear Networks: From Balanced to Imbalanced Data
Hien Dang
Tho Tran
T. Nguyen
Hung The Tran
Nhat Ho
Hung Tran
55
30
0
01 Jan 2023
Perturbation Analysis of Neural Collapse
Perturbation Analysis of Neural Collapse
Tom Tirer
Haoxiang Huang
Jonathan Niles-Weed
AAML
66
26
0
29 Oct 2022
Continual Learning by Modeling Intra-Class Variation
Continual Learning by Modeling Intra-Class Variation
L. Yu
Tianyang Hu
Lanqing Hong
Zhen Liu
Adrian Weller
Weiyang Liu
CLL
72
13
0
11 Oct 2022
Are All Losses Created Equal: A Neural Collapse Perspective
Are All Losses Created Equal: A Neural Collapse Perspective
Jinxin Zhou
Chong You
Xiao Li
Kangning Liu
Sheng Liu
Qing Qu
Zhihui Zhu
55
63
0
04 Oct 2022
Neural Collapse with Normalized Features: A Geometric Analysis over the
  Riemannian Manifold
Neural Collapse with Normalized Features: A Geometric Analysis over the Riemannian Manifold
Can Yaras
Peng Wang
Zhihui Zhu
Laura Balzano
Qing Qu
41
44
0
19 Sep 2022
Imbalance Trouble: Revisiting Neural-Collapse Geometry
Imbalance Trouble: Revisiting Neural-Collapse Geometry
Christos Thrampoulidis
Ganesh Ramachandra Kini
V. Vakilian
Tina Behnia
49
71
0
10 Aug 2022
Neural Collapse Inspired Attraction-Repulsion-Balanced Loss for
  Imbalanced Learning
Neural Collapse Inspired Attraction-Repulsion-Balanced Loss for Imbalanced Learning
Liang Xie
Yibo Yang
Deng Cai
Xiaofei He
41
45
0
19 Apr 2022
On the Optimization Landscape of Neural Collapse under MSE Loss: Global
  Optimality with Unconstrained Features
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
61
101
0
02 Mar 2022
Extended Unconstrained Features Model for Exploring Deep Neural Collapse
Extended Unconstrained Features Model for Exploring Deep Neural Collapse
Tom Tirer
Joan Bruna
AAML
23
97
0
16 Feb 2022
On the Role of Neural Collapse in Transfer Learning
On the Role of Neural Collapse in Transfer Learning
Tomer Galanti
András Gyorgy
Marcus Hutter
SSL
47
90
0
30 Dec 2021
Neural Collapse Under MSE Loss: Proximity to and Dynamics on the Central
  Path
Neural Collapse Under MSE Loss: Proximity to and Dynamics on the Central Path
X. Y. Han
Vardan Papyan
D. Donoho
AAML
56
143
0
03 Jun 2021
A Geometric Analysis of Neural Collapse with Unconstrained Features
A Geometric Analysis of Neural Collapse with Unconstrained Features
Zhihui Zhu
Tianyu Ding
Jinxin Zhou
Xiao Li
Chong You
Jeremias Sulam
Qing Qu
58
202
0
06 May 2021
Exploring Deep Neural Networks via Layer-Peeled Model: Minority Collapse
  in Imbalanced Training
Exploring Deep Neural Networks via Layer-Peeled Model: Minority Collapse in Imbalanced Training
Cong Fang
Hangfeng He
Qi Long
Weijie J. Su
FAtt
143
170
0
29 Jan 2021
Explicit regularization and implicit bias in deep network classifiers
  trained with the square loss
Explicit regularization and implicit bias in deep network classifiers trained with the square loss
T. Poggio
Q. Liao
22
42
0
31 Dec 2020
On the emergence of simplex symmetry in the final and penultimate layers
  of neural network classifiers
On the emergence of simplex symmetry in the final and penultimate layers of neural network classifiers
E. Weinan
Stephan Wojtowytsch
56
44
0
10 Dec 2020
Neural collapse with unconstrained features
Neural collapse with unconstrained features
D. Mixon
Hans Parshall
Jianzong Pi
46
118
0
23 Nov 2020
Prevalence of Neural Collapse during the terminal phase of deep learning
  training
Prevalence of Neural Collapse during the terminal phase of deep learning training
Vardan Papyan
Xuemei Han
D. Donoho
97
563
0
18 Aug 2020
Does label smoothing mitigate label noise?
Does label smoothing mitigate label noise?
Michal Lukasik
Srinadh Bhojanapalli
A. Menon
Surinder Kumar
NoLa
106
348
0
05 Mar 2020
When Does Label Smoothing Help?
When Does Label Smoothing Help?
Rafael Müller
Simon Kornblith
Geoffrey E. Hinton
UQCV
134
1,931
0
06 Jun 2019
The Expressive Power of Neural Networks: A View from the Width
The Expressive Power of Neural Networks: A View from the Width
Zhou Lu
Hongming Pu
Feicheng Wang
Zhiqiang Hu
Liwei Wang
67
886
0
08 Sep 2017
On Calibration of Modern Neural Networks
On Calibration of Modern Neural Networks
Chuan Guo
Geoff Pleiss
Yu Sun
Kilian Q. Weinberger
UQCV
199
5,774
0
14 Jun 2017
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
1.4K
192,638
0
10 Dec 2015
Rethinking the Inception Architecture for Computer Vision
Rethinking the Inception Architecture for Computer Vision
Christian Szegedy
Vincent Vanhoucke
Sergey Ioffe
Jonathon Shlens
Z. Wojna
3DV
BDL
495
27,231
0
02 Dec 2015
Provable approximation properties for deep neural networks
Provable approximation properties for deep neural networks
Uri Shaham
A. Cloninger
Ronald R. Coifman
91
230
0
24 Sep 2015
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