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What is the Effect of Importance Weighting in Deep Learning?

What is the Effect of Importance Weighting in Deep Learning?

8 December 2018
Jonathon Byrd
Zachary Chase Lipton
ArXivPDFHTML

Papers citing "What is the Effect of Importance Weighting in Deep Learning?"

24 / 124 papers shown
Title
Variational Disentanglement for Rare Event Modeling
Variational Disentanglement for Rare Event Modeling
Zidi Xiu
Chenyang Tao
M. Gao
Connor Davis
B. Goldstein
Ricardo Henao
CML
DRL
32
6
0
17 Sep 2020
PCPL: Predicate-Correlation Perception Learning for Unbiased Scene Graph
  Generation
PCPL: Predicate-Correlation Perception Learning for Unbiased Scene Graph Generation
Shaotian Yan
Chen Shen
Zhongming Jin
Jianqiang Huang
Rongxin Jiang
Yao-wu Chen
Xiansheng Hua
34
131
0
02 Sep 2020
Balanced Activation for Long-tailed Visual Recognition
Balanced Activation for Long-tailed Visual Recognition
Jiawei Ren
Cunjun Yu
Zhongang Cai
Haiyu Zhao
VLM
10
2
0
24 Aug 2020
Memory-based Jitter: Improving Visual Recognition on Long-tailed Data
  with Diversity In Memory
Memory-based Jitter: Improving Visual Recognition on Long-tailed Data with Diversity In Memory
Jialun Liu
Jingwei Zhang
Yi yang
Wenhui Li
Chi Zhang
Yifan Sun
28
39
0
22 Aug 2020
Forest R-CNN: Large-Vocabulary Long-Tailed Object Detection and Instance
  Segmentation
Forest R-CNN: Large-Vocabulary Long-Tailed Object Detection and Instance Segmentation
Jialian Wu
Liangchen Song
Tiancai Wang
Qian Zhang
Junsong Yuan
ObjD
24
72
0
13 Aug 2020
The Devil is in Classification: A Simple Framework for Long-tail Object
  Detection and Instance Segmentation
The Devil is in Classification: A Simple Framework for Long-tail Object Detection and Instance Segmentation
Tao Wang
Yu Li
Bingyi Kang
Junnan Li
Jun Hao Liew
Sheng Tang
Guosheng Lin
Jiashi Feng
ISeg
19
176
0
23 Jul 2020
Balanced Meta-Softmax for Long-Tailed Visual Recognition
Balanced Meta-Softmax for Long-Tailed Visual Recognition
Jiawei Ren
Cunjun Yu
Shunan Sheng
Xiao Ma
Haiyu Zhao
Shuai Yi
Hongsheng Li
170
552
0
21 Jul 2020
Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed
  Datasets
Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets
Tong Wu
Qingqiu Huang
Ziwei Liu
Yu Wang
Dahua Lin
27
228
0
19 Jul 2020
Long-tail learning via logit adjustment
Long-tail learning via logit adjustment
A. Menon
Sadeep Jayasumana
A. S. Rawat
Himanshu Jain
Andreas Veit
Sanjiv Kumar
65
688
0
14 Jul 2020
Remix: Rebalanced Mixup
Remix: Rebalanced Mixup
Hsin-Ping Chou
Shih-Chieh Chang
Jia-Yu Pan
Wei Wei
Da-Cheng Juan
38
232
0
08 Jul 2020
Rethinking the Value of Labels for Improving Class-Imbalanced Learning
Rethinking the Value of Labels for Improving Class-Imbalanced Learning
Yuzhe Yang
Zhi Xu
SSL
20
402
0
13 Jun 2020
Rethinking Importance Weighting for Deep Learning under Distribution
  Shift
Rethinking Importance Weighting for Deep Learning under Distribution Shift
Tongtong Fang
Nan Lu
Gang Niu
Masashi Sugiyama
33
137
0
08 Jun 2020
Rethinking of Pedestrian Attribute Recognition: Realistic Datasets with
  Efficient Method
Rethinking of Pedestrian Attribute Recognition: Realistic Datasets with Efficient Method
Jian Jia
Houjing Huang
Wenjie Yang
Xiaotang Chen
Kaiqi Huang
24
44
0
25 May 2020
An Investigation of Why Overparameterization Exacerbates Spurious
  Correlations
An Investigation of Why Overparameterization Exacerbates Spurious Correlations
Shiori Sagawa
Aditi Raghunathan
Pang Wei Koh
Percy Liang
155
372
0
09 May 2020
A Unified View of Label Shift Estimation
A Unified View of Label Shift Estimation
Saurabh Garg
Yifan Wu
Sivaraman Balakrishnan
Zachary Chase Lipton
24
140
0
17 Mar 2020
Distributionally Robust Deep Learning using Hardness Weighted Sampling
Distributionally Robust Deep Learning using Hardness Weighted Sampling
Lucas Fidon
Michael Aertsen
Thomas Deprest
Doaa Emam
Frédéric Guffens
...
Andrew Melbourne
Sébastien Ourselin
Jan Deprest
Georg Langs
Tom Kamiel Magda Vercauteren
OOD
27
10
0
08 Jan 2020
Identifying and Compensating for Feature Deviation in Imbalanced Deep
  Learning
Identifying and Compensating for Feature Deviation in Imbalanced Deep Learning
Han-Jia Ye
Hong-You Chen
De-Chuan Zhan
Wei-Lun Chao
39
99
0
06 Jan 2020
BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed
  Visual Recognition
BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed Visual Recognition
Boyan Zhou
Quan Cui
Xiu-Shen Wei
Zhao-Min Chen
253
784
0
05 Dec 2019
Distributionally Robust Neural Networks for Group Shifts: On the
  Importance of Regularization for Worst-Case Generalization
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
16
1,200
0
20 Nov 2019
Fair Generative Modeling via Weak Supervision
Fair Generative Modeling via Weak Supervision
Kristy Choi
Aditya Grover
Trisha Singh
Rui Shu
Stefano Ermon
36
133
0
26 Oct 2019
Bias Correction of Learned Generative Models using Likelihood-Free
  Importance Weighting
Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting
Aditya Grover
Jiaming Song
Alekh Agarwal
Kenneth Tran
Ashish Kapoor
Eric Horvitz
Stefano Ermon
26
123
0
23 Jun 2019
Lexicographic and Depth-Sensitive Margins in Homogeneous and
  Non-Homogeneous Deep Models
Lexicographic and Depth-Sensitive Margins in Homogeneous and Non-Homogeneous Deep Models
Mor Shpigel Nacson
Suriya Gunasekar
Jason D. Lee
Nathan Srebro
Daniel Soudry
33
92
0
17 May 2019
Assuring the Machine Learning Lifecycle: Desiderata, Methods, and
  Challenges
Assuring the Machine Learning Lifecycle: Desiderata, Methods, and Challenges
Rob Ashmore
R. Calinescu
Colin Paterson
AI4TS
34
116
0
10 May 2019
Maximum Likelihood with Bias-Corrected Calibration is Hard-To-Beat at
  Label Shift Adaptation
Maximum Likelihood with Bias-Corrected Calibration is Hard-To-Beat at Label Shift Adaptation
Amr M. Alexandari
A. Kundaje
Avanti Shrikumar
21
9
0
21 Jan 2019
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