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C-Mixup: Improving Generalization in Regression

C-Mixup: Improving Generalization in Regression

11 October 2022
Huaxiu Yao
Yiping Wang
Linjun Zhang
James Zou
Chelsea Finn
    UQCV
    OOD
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Papers citing "C-Mixup: Improving Generalization in Regression"

21 / 21 papers shown
Title
Language-Driven Dual Style Mixing for Single-Domain Generalized Object Detection
Language-Driven Dual Style Mixing for Single-Domain Generalized Object Detection
Hongda Qin
Xiao Lu
Zhiyong Wei
Yihong Cao
Kailun Yang
Ningjiang Chen
ObjD
MLLM
VLM
31
0
0
12 May 2025
Sample Selection via Contrastive Fragmentation for Noisy Label Regression
Sample Selection via Contrastive Fragmentation for Noisy Label Regression
C. Kim
Sangwoo Moon
Jihwan Moon
Dongyeon Woo
Gunhee Kim
NoLa
57
0
0
25 Feb 2025
RC-Mixup: A Data Augmentation Strategy against Noisy Data for Regression
  Tasks
RC-Mixup: A Data Augmentation Strategy against Noisy Data for Regression Tasks
Seonghyeon Hwang
Minsu Kim
Steven Euijong Whang
NoLa
35
2
0
28 May 2024
StarLKNet: Star Mixup with Large Kernel Networks for Palm Vein
  Identification
StarLKNet: Star Mixup with Large Kernel Networks for Palm Vein Identification
Xin Jin
Hongyu Zhu
M. El-Yacoubi
Hongchao Liao
Huafeng Qin
Yun Jiang
39
6
0
21 May 2024
Out of the Ordinary: Spectrally Adapting Regression for Covariate Shift
Out of the Ordinary: Spectrally Adapting Regression for Covariate Shift
Benjamin Eyre
Elliot Creager
David Madras
Antonio Torralba
Katherine Heller
OOD
OODD
40
1
0
29 Dec 2023
NNG-Mix: Improving Semi-supervised Anomaly Detection with Pseudo-anomaly
  Generation
NNG-Mix: Improving Semi-supervised Anomaly Detection with Pseudo-anomaly Generation
Hao Dong
Gaëtan Frusque
Yue Zhao
Eleni Chatzi
Olga Fink
AAML
39
5
0
20 Nov 2023
Tailoring Mixup to Data for Calibration
Tailoring Mixup to Data for Calibration
Quentin Bouniot
Pavlo Mozharovskyi
Florence dÁlché-Buc
61
1
0
02 Nov 2023
SemiReward: A General Reward Model for Semi-supervised Learning
SemiReward: A General Reward Model for Semi-supervised Learning
Siyuan Li
Weiyang Jin
Zedong Wang
Fang Wu
Zicheng Liu
Cheng Tan
Stan Z. Li
38
9
0
04 Oct 2023
ADASSM: Adversarial Data Augmentation in Statistical Shape Models From
  Images
ADASSM: Adversarial Data Augmentation in Statistical Shape Models From Images
Mokshagna Sai Teja Karanam
Tushar Kataria
Krithika S. Iyer
Shireen Y. Elhabian
MedIm
21
4
0
06 Jul 2023
R-Mixup: Riemannian Mixup for Biological Networks
R-Mixup: Riemannian Mixup for Biological Networks
Xuan Kan
Zimu Li
Hejie Cui
Yue Yu
Ran Xu
Shaojun Yu
Zilong Zhang
Ying Guo
Carl Yang
35
6
0
05 Jun 2023
Infinite Class Mixup
Infinite Class Mixup
Thomas Mensink
Pascal Mettes
29
2
0
17 May 2023
Improving Domain Generalization with Domain Relations
Improving Domain Generalization with Domain Relations
Huaxiu Yao
Xinyu Yang
Xinyi Pan
Shengchao Liu
Pang Wei Koh
Chelsea Finn
OOD
AI4CE
52
8
0
06 Feb 2023
Rank-N-Contrast: Learning Continuous Representations for Regression
Rank-N-Contrast: Learning Continuous Representations for Regression
Kaiwen Zha
Peng Cao
Jeany Son
Yuzhe Yang
Dina Katabi
CML
64
37
0
03 Oct 2022
Harnessing Hard Mixed Samples with Decoupled Regularizer
Harnessing Hard Mixed Samples with Decoupled Regularizer
Zicheng Liu
Siyuan Li
Ge Wang
Cheng Tan
Lirong Wu
Stan Z. Li
59
18
0
21 Mar 2022
Gradient Matching for Domain Generalization
Gradient Matching for Domain Generalization
Yuge Shi
Jeffrey S. Seely
Philip Torr
Siddharth Narayanaswamy
Awni Y. Hannun
Nicolas Usunier
Gabriel Synnaeve
OOD
227
246
0
20 Apr 2021
Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity
Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity
Jang-Hyun Kim
Wonho Choo
Hosan Jeong
Hyun Oh Song
205
176
0
05 Feb 2021
Improving Generalization in Reinforcement Learning with Mixture
  Regularization
Improving Generalization in Reinforcement Learning with Mixture Regularization
Kaixin Wang
Bingyi Kang
Jie Shao
Jiashi Feng
109
117
0
21 Oct 2020
Deep Domain-Adversarial Image Generation for Domain Generalisation
Deep Domain-Adversarial Image Generation for Domain Generalisation
Kaiyang Zhou
Yongxin Yang
Timothy M. Hospedales
Tao Xiang
OOD
220
405
0
12 Mar 2020
Out-of-Distribution Generalization via Risk Extrapolation (REx)
Out-of-Distribution Generalization via Risk Extrapolation (REx)
David M. Krueger
Ethan Caballero
J. Jacobsen
Amy Zhang
Jonathan Binas
Dinghuai Zhang
Rémi Le Priol
Aaron Courville
OOD
215
901
0
02 Mar 2020
Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness
  of MAML
Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML
Aniruddh Raghu
M. Raghu
Samy Bengio
Oriol Vinyals
186
640
0
19 Sep 2019
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,145
0
06 Jun 2015
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