AutoBalance: Optimized Loss Functions for Imbalanced Data

4 January 2022

Mingchen Li

Xuechen Zhang

Christos Thrampoulidis

Jiasi Chen

Samet Oymak

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Papers citing "AutoBalance: Optimized Loss Functions for Imbalanced Data"

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Title
2D-Curri-DPO: Two-Dimensional Curriculum Learning for Direct Preference Optimization Mengyang Li Zhong Zhang 64 1 0 10 Apr 2025
Generalization Guarantees for Neural Architecture Search with Train-Validation Split Samet Oymak Mingchen Li Mahdi Soltanolkotabi AI4CE OOD 60 15 0 29 Apr 2021
Label-Imbalanced and Group-Sensitive Classification under Overparameterization Ganesh Ramachandra Kini Orestis Paraskevas Samet Oymak Christos Thrampoulidis 66 96 0 02 Mar 2021
How Important is the Train-Validation Split in Meta-Learning? Yu Bai Minshuo Chen Pan Zhou T. Zhao Jason D. Lee Sham Kakade Haiquan Wang Caiming Xiong 66 53 0 12 Oct 2020
Long-tail learning via logit adjustment A. Menon Sadeep Jayasumana A. S. Rawat Himanshu Jain Andreas Veit Sanjiv Kumar 120 709 0 14 Jul 2020
Theory-Inspired Path-Regularized Differential Network Architecture Search Pan Zhou Caiming Xiong R. Socher Guosheng Lin 30 55 0 30 Jun 2020
Meta Approach to Data Augmentation Optimization Ryuichiro Hataya Jan Zdenek Kazuki Yoshizoe Hideki Nakayama 79 35 0 14 Jun 2020
On the Role of Dataset Quality and Heterogeneity in Model Confidence Yuan Zhao Jiasi Chen Samet Oymak 43 14 0 23 Feb 2020
Identifying and Compensating for Feature Deviation in Imbalanced Deep Learning Han-Jia Ye Hong-You Chen De-Chuan Zhan Wei-Lun Chao 90 101 0 06 Jan 2020
To Balance or Not to Balance: A Simple-yet-Effective Approach for Learning with Long-Tailed Distributions Junjie Zhang Lingqiao Liu Peng Wang Chunhua Shen 61 25 0 10 Dec 2019
BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed Visual Recognition Boyan Zhou Quan Cui Xiu-Shen Wei Zhao-Min Chen 288 800 0 05 Dec 2019
Adjusting Decision Boundary for Class Imbalanced Learning Byungju Kim Junmo Kim 117 76 0 04 Dec 2019
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization Shiori Sagawa Pang Wei Koh Tatsunori B. Hashimoto Percy Liang OOD 97 1,241 0 20 Nov 2019
Faster AutoAugment: Learning Augmentation Strategies using Backpropagation Ryuichiro Hataya Jan Zdenek Kazuki Yoshizoe Hideki Nakayama 74 205 0 16 Nov 2019
Optimizing Millions of Hyperparameters by Implicit Differentiation Jonathan Lorraine Paul Vicol David Duvenaud DD 114 415 0 06 Nov 2019
Decoupling Representation and Classifier for Long-Tailed Recognition Bingyi Kang Saining Xie Marcus Rohrbach Zhicheng Yan Albert Gordo Jiashi Feng Yannis Kalantidis OODD 177 1,219 0 21 Oct 2019
Polylogarithmic width suffices for gradient descent to achieve arbitrarily small test error with shallow ReLU networks Ziwei Ji Matus Telgarsky 59 178 0 26 Sep 2019
Learning an Adaptive Learning Rate Schedule Zhen Xu Andrew M. Dai Jonas Kemp Luke Metz 62 62 0 20 Sep 2019
Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss Kaidi Cao Colin Wei Adrien Gaidon Nikos Arechiga Tengyu Ma 124 1,602 0 18 Jun 2019
Does Learning Require Memorization? A Short Tale about a Long Tail Vitaly Feldman TDI 123 494 0 12 Jun 2019
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks Mingxing Tan Quoc V. Le 3DV MedIm 139 18,134 0 28 May 2019
Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules Daniel Ho Eric Liang Ion Stoica Pieter Abbeel Xi Chen 70 404 0 14 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 619 4,780 0 13 May 2019
Fast AutoAugment Sungbin Lim Ildoo Kim Taesup Kim Chiheon Kim Sungwoong Kim 97 595 0 01 May 2019
Self-Tuning Networks: Bilevel Optimization of Hyperparameters using Structured Best-Response Functions M. Mackay Paul Vicol Jonathan Lorraine David Duvenaud Roger C. Grosse 78 164 0 07 Mar 2019
Towards moderate overparameterization: global convergence guarantees for training shallow neural networks Samet Oymak Mahdi Soltanolkotabi 50 321 0 12 Feb 2019
Fairness risk measures Robert C. Williamson A. Menon FaML 141 141 0 24 Jan 2019
Striking the Right Balance with Uncertainty Salman Khan Munawar Hayat Waqas Zamir Jianbing Shen Ling Shao 75 174 0 22 Jan 2019
Class-Balanced Loss Based on Effective Number of Samples Huayu Chen Menglin Jia Nayeon Lee Yang Song Serge J. Belongie 198 2,281 0 16 Jan 2019
SNAS: Stochastic Neural Architecture Search Sirui Xie Hehui Zheng Chunxiao Liu Liang Lin 83 936 0 24 Dec 2018
What is the Effect of Importance Weighting in Deep Learning? Jonathon Byrd Zachary Chase Lipton 89 464 0 08 Dec 2018
Gradient Descent Finds Global Minima of Deep Neural Networks S. Du Jason D. Lee Haochuan Li Liwei Wang Masayoshi Tomizuka ODL 201 1,135 0 09 Nov 2018
Truncated Back-propagation for Bilevel Optimization Amirreza Shaban Ching-An Cheng Nathan Hatch Byron Boots 101 266 0 25 Oct 2018
Deep Bilevel Learning Simon Jenni Paolo Favaro NoLa 62 115 0 05 Sep 2018
BlockQNN: Efficient Block-wise Neural Network Architecture Generation Zhaobai Zhong Zichen Yang Boyang Deng Junjie Yan Wei Wu Jing Shao Cheng-Lin Liu 65 116 0 16 Aug 2018
DARTS: Differentiable Architecture Search Hanxiao Liu Karen Simonyan Yiming Yang 199 4,355 0 24 Jun 2018
Bilevel Programming for Hyperparameter Optimization and Meta-Learning Luca Franceschi P. Frasconi Saverio Salzo Riccardo Grazzi Massimiliano Pontil 176 728 0 13 Jun 2018
AutoAugment: Learning Augmentation Policies from Data E. D. Cubuk Barret Zoph Dandelion Mané Vijay Vasudevan Quoc V. Le 123 1,772 0 24 May 2018
Exploring the Limits of Weakly Supervised Pretraining D. Mahajan Ross B. Girshick Vignesh Ramanathan Kaiming He Manohar Paluri Yixuan Li Ashwin R. Bharambe Laurens van der Maaten VLM 185 1,368 0 02 May 2018
Imbalanced Deep Learning by Minority Class Incremental Rectification Qi Dong S. Gong Xiatian Zhu 44 329 0 28 Apr 2018
Reviving and Improving Recurrent Back-Propagation Renjie Liao Yuwen Xiong Ethan Fetaya Lisa Zhang Kijung Yoon Xaq Pitkow R. Urtasun R. Zemel BDL 72 120 0 16 Mar 2018
A Kernel Theory of Modern Data Augmentation Tri Dao Albert Gu Alexander J. Ratner Virginia Smith Christopher De Sa Christopher Ré 100 193 0 16 Mar 2018
Empirical Risk Minimization under Fairness Constraints Michele Donini L. Oneto Shai Ben-David John Shawe-Taylor Massimiliano Pontil FaML 76 444 0 23 Feb 2018
mixup: Beyond Empirical Risk Minimization Hongyi Zhang Moustapha Cissé Yann N. Dauphin David Lopez-Paz NoLa 280 9,764 0 25 Oct 2017
A systematic study of the class imbalance problem in convolutional neural networks Mateusz Buda A. Maki Maciej A. Mazurowski 213 2,366 0 15 Oct 2017
Improved Regularization of Convolutional Neural Networks with Cutout Terrance Devries Graham W. Taylor 109 3,765 0 15 Aug 2017
On Calibration of Modern Neural Networks Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger UQCV 299 5,833 0 14 Jun 2017
Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour Priya Goyal Piotr Dollár Ross B. Girshick P. Noordhuis Lukasz Wesolowski Aapo Kyrola Andrew Tulloch Yangqing Jia Kaiming He 3DH 126 3,681 0 08 Jun 2017
A Review on Bilevel Optimization: From Classical to Evolutionary Approaches and Applications Ankur Sinha P. Malo Kalyanmoy Deb 46 756 0 17 May 2017
Deep Over-sampling Framework for Classifying Imbalanced Data S. Ando Chun-Yuan Huang 45 180 0 25 Apr 2017