For Better or For Worse? Learning Minimum Variance Features With Label Augmentation

10 February 2024

Papers citing "For Better or For Worse? Learning Minimum Variance Features With Label Augmentation"

41 / 41 papers shown

Title
On the Limitations of Temperature Scaling for Distributions with Overlaps Muthuraman Chidambaram Rong Ge UQCV 52 4 0 01 Jun 2023
Provable Benefit of Mixup for Finding Optimal Decision Boundaries Junsoo Oh Chulee Yun 48 6 0 01 Jun 2023
The Benefits of Mixup for Feature Learning Difan Zou Yuan Cao Yuan-Fang Li Quanquan Gu MLT 16 20 0 15 Mar 2023
Scaling Vision Transformers to 22 Billion Parameters Mostafa Dehghani Josip Djolonga Basil Mustafa Piotr Padlewski Jonathan Heek ... Mario Luvcić Xiaohua Zhai Daniel Keysers Jeremiah Harmsen N. Houlsby MLLM 128 585 0 10 Feb 2023
Provably Learning Diverse Features in Multi-View Data with Midpoint Mixup Muthuraman Chidambaram Xiang Wang Chenwei Wu Rong Ge MLT 53 9 0 24 Oct 2022
A Unified Analysis of Mixed Sample Data Augmentation: A Loss Function Perspective Chanwoo Park Sangdoo Yun Sanghyuk Chun AAML 51 32 0 21 Aug 2022
Data Augmentation vs. Equivariant Networks: A Theory of Generalization on Dynamics Forecasting Rui Wang Robin Walters Rose Yu 33 14 0 19 Jun 2022
Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time Mitchell Wortsman Gabriel Ilharco S. Gadre Rebecca Roelofs Raphael Gontijo-Lopes ... Hongseok Namkoong Ali Farhadi Y. Carmon Simon Kornblith Ludwig Schmidt MoMe 108 953 1 10 Mar 2022
Data Augmentation as Feature Manipulation Ruoqi Shen Sébastien Bubeck Suriya Gunasekar MLT 34 16 0 03 Mar 2022
Sample Efficiency of Data Augmentation Consistency Regularization Shuo Yang Yijun Dong Rachel A. Ward Inderjit S. Dhillon Sujay Sanghavi Qi Lei AAML 43 17 0 24 Feb 2022
Towards Understanding the Data Dependency of Mixup-style Training Muthuraman Chidambaram Xiang Wang Yuzheng Hu Chenwei Wu Rong Ge UQCV 63 24 0 14 Oct 2021
Noisy Feature Mixup Soon Hoe Lim N. Benjamin Erichson Francisco Utrera Winnie Xu Michael W. Mahoney AAML 73 37 0 05 Oct 2021
Mixup Decoding for Diverse Machine Translation Jicheng Li Pengzhi Gao Xuanfu Wu Yang Feng Zhongjun He Hua Wu Haifeng Wang 43 14 0 08 Sep 2021
To Smooth or Not? When Label Smoothing Meets Noisy Labels Jiaheng Wei Hangyu Liu Tongliang Liu Gang Niu Masashi Sugiyama Yang Liu NoLa 32 69 0 08 Jun 2021
Diversifying Dialog Generation via Adaptive Label Smoothing Yida Wang Yinhe Zheng Yong Jiang Minlie Huang 51 37 0 30 May 2021
Learning with invariances in random features and kernel models Song Mei Theodor Misiakiewicz Andrea Montanari OOD 78 90 0 25 Feb 2021
When and How Mixup Improves Calibration Linjun Zhang Zhun Deng Kenji Kawaguchi James Zou UQCV 45 67 0 11 Feb 2021
Understanding Instance-Level Label Noise: Disparate Impacts and Treatments Yang Liu NoLa 16 35 0 10 Feb 2021
How Data Augmentation affects Optimization for Linear Regression Boris Hanin Yi Sun 42 16 0 21 Oct 2020
How Does Mixup Help With Robustness and Generalization? Linjun Zhang Zhun Deng Kenji Kawaguchi Amirata Ghorbani James Zou AAML 64 247 0 09 Oct 2020
Puzzle Mix: Exploiting Saliency and Local Statistics for Optimal Mixup Jang-Hyun Kim Wonho Choo Hyun Oh Song AAML 55 387 0 15 Sep 2020
Towards Understanding Label Smoothing Yi Tian Xu Yuanhong Xu Qi Qian Hao Li Rong Jin UQCV 28 41 0 20 Jun 2020
SaliencyMix: A Saliency Guided Data Augmentation Strategy for Better Regularization A. Uddin Sirazam Monira Wheemyung Shin TaeChoong Chung Sung-Ho Bae 37 228 0 02 Jun 2020
On the Generalization Effects of Linear Transformations in Data Augmentation Sen Wu Hongyang R. Zhang Gregory Valiant Christopher Ré 35 77 0 02 May 2020
Does label smoothing mitigate label noise? Michal Lukasik Srinadh Bhojanapalli A. Menon Surinder Kumar NoLa 108 348 0 05 Mar 2020
Regularization via Structural Label Smoothing Weizhi Li Gautam Dasarathy Visar Berisha UQCV 42 51 0 07 Jan 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 277 42,038 0 03 Dec 2019
RandAugment: Practical automated data augmentation with a reduced search space E. D. Cubuk Barret Zoph Jonathon Shlens Quoc V. Le MQ 191 3,458 0 30 Sep 2019
Invariant Risk Minimization Martín Arjovsky Léon Bottou Ishaan Gulrajani David Lopez-Paz OOD 155 2,190 0 05 Jul 2019
When Does Label Smoothing Help? Rafael Müller Simon Kornblith Geoffrey E. Hinton UQCV 137 1,931 0 06 Jun 2019
On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks S. Thulasidasan Gopinath Chennupati J. Bilmes Tanmoy Bhattacharya S. Michalak UQCV 62 535 0 27 May 2019
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features Sangdoo Yun Dongyoon Han Seong Joon Oh Sanghyuk Chun Junsuk Choe Y. Yoo OOD 581 4,735 0 13 May 2019
Does Data Augmentation Lead to Positive Margin? Shashank Rajput Zhili Feng Zachary B. Charles Po-Ling Loh Dimitris Papailiopoulos 33 38 0 08 May 2019
MixUp as Locally Linear Out-Of-Manifold Regularization Hongyu Guo Yongyi Mao Richong Zhang 48 321 0 07 Sep 2018
A Kernel Theory of Modern Data Augmentation Tri Dao Albert Gu Alexander J. Ratner Virginia Smith Christopher De Sa Christopher Ré 90 192 0 16 Mar 2018
The Implicit Bias of Gradient Descent on Separable Data Daniel Soudry Elad Hoffer Mor Shpigel Nacson Suriya Gunasekar Nathan Srebro 74 908 0 27 Oct 2017
mixup: Beyond Empirical Risk Minimization Hongyi Zhang Moustapha Cissé Yann N. Dauphin David Lopez-Paz NoLa 243 9,687 0 25 Oct 2017
Attention Is All You Need Ashish Vaswani Noam M. Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan Gomez Lukasz Kaiser Illia Polosukhin 3DV 453 129,831 0 12 Jun 2017
Regularizing Neural Networks by Penalizing Confident Output Distributions Gabriel Pereyra George Tucker J. Chorowski Lukasz Kaiser Geoffrey E. Hinton NoLa 114 1,133 0 23 Jan 2017
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 Christian Szegedy Vincent Vanhoucke Sergey Ioffe Jonathon Shlens Z. Wojna 3DV BDL 497 27,231 0 02 Dec 2015