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A Comparative Survey of Deep Active Learning

A Comparative Survey of Deep Active Learning

25 March 2022
Xueying Zhan
Qingzhong Wang
Kuan-Hao Huang
Haoyi Xiong
Dejing Dou
Antoni B. Chan
    FedML
    HAI
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Papers citing "A Comparative Survey of Deep Active Learning"

48 / 48 papers shown
Title
Deep Active Learning in the Open World
Deep Active Learning in the Open World
Tian Xie
Jifan Zhang
Haoyue Bai
R. Nowak
VLM
357
2
0
10 Nov 2024
AutoAL: Automated Active Learning with Differentiable Query Strategy Search
AutoAL: Automated Active Learning with Differentiable Query Strategy Search
Yifeng Wang
Xueying Zhan
Siyu Huang
OOD
93
0
0
17 Oct 2024
DELTA: Dual Consistency Delving with Topological Uncertainty for Active Graph Domain Adaptation
DELTA: Dual Consistency Delving with Topological Uncertainty for Active Graph Domain Adaptation
Pengyun Wang
Yadi Cao
Chris Russell
Yanxin Shen
Junyu Luo
Ming Zhang
Siyu Heng
Zhiyuan Ning
66
1
0
13 Sep 2024
Avoid Wasted Annotation Costs in Open-set Active Learning with Pre-trained Vision-Language Model
Avoid Wasted Annotation Costs in Open-set Active Learning with Pre-trained Vision-Language Model
Jaehyuk Heo
Pilsung Kang
VLM
47
1
0
09 Aug 2024
An Empirical Study on Distribution Shift Robustness From the Perspective
  of Pre-Training and Data Augmentation
An Empirical Study on Distribution Shift Robustness From the Perspective of Pre-Training and Data Augmentation
Ziquan Liu
Yi Tian Xu
Yuanhong Xu
Qi Qian
Hao Li
Rong Jin
Xiangyang Ji
Antoni B. Chan
OOD
57
15
0
25 May 2022
Towards General and Efficient Active Learning
Towards General and Efficient Active Learning
Yichen Xie
Masayoshi Tomizuka
Wei Zhan
VLM
53
10
0
15 Dec 2021
Boosting Active Learning via Improving Test Performance
Boosting Active Learning via Improving Test Performance
Tianyang Wang
Xingjian Li
Pengkun Yang
Guosheng Hu
Xiangrui Zeng
Siyu Huang
Chengzhong Xu
Min Xu
49
33
0
10 Dec 2021
DeepAL: Deep Active Learning in Python
DeepAL: Deep Active Learning in Python
Kuan-Hao Huang
AI4CE
72
17
0
30 Nov 2021
Batch Active Learning at Scale
Batch Active Learning at Scale
Gui Citovsky
Giulia DeSalvo
Claudio Gentile
Lazaros Karydas
Anand Rajagopalan
Afshin Rostamizadeh
Sanjiv Kumar
55
154
0
29 Jul 2021
Mind Your Outliers! Investigating the Negative Impact of Outliers on
  Active Learning for Visual Question Answering
Mind Your Outliers! Investigating the Negative Impact of Outliers on Active Learning for Visual Question Answering
Siddharth Karamcheti
Ranjay Krishna
Li Fei-Fei
Christopher D. Manning
73
92
0
06 Jul 2021
Multiple-criteria Based Active Learning with Fixed-size Determinantal
  Point Processes
Multiple-criteria Based Active Learning with Fixed-size Determinantal Point Processes
Xueying Zhan
Qing Li
Antoni B. Chan
33
8
0
04 Jul 2021
SIMILAR: Submodular Information Measures Based Active Learning In
  Realistic Scenarios
SIMILAR: Submodular Information Measures Based Active Learning In Realistic Scenarios
Suraj Kothawade
Nathan Beck
Krishnateja Killamsetty
Rishabh K. Iyer
38
106
0
01 Jul 2021
A survey of active learning algorithms for supervised remote sensing
  image classification
A survey of active learning algorithms for supervised remote sensing image classification
D. Tuia
Michele Volpi
Loris Copa
M. Kanevski
Jordi Munoz-Marí
34
525
0
15 Apr 2021
Active Learning for Deep Object Detection via Probabilistic Modeling
Active Learning for Deep Object Detection via Probabilistic Modeling
Jiwoong Choi
Ismail Elezi
Hyuk-Jae Lee
C. Farabet
J. Álvarez
50
122
0
30 Mar 2021
GLISTER: Generalization based Data Subset Selection for Efficient and
  Robust Learning
GLISTER: Generalization based Data Subset Selection for Efficient and Robust Learning
Krishnateja Killamsetty
D. Sivasubramanian
Ganesh Ramakrishnan
Rishabh Iyer University of Texas at Dallas
58
209
0
19 Dec 2020
WILDS: A Benchmark of in-the-Wild Distribution Shifts
WILDS: A Benchmark of in-the-Wild Distribution Shifts
Pang Wei Koh
Shiori Sagawa
Henrik Marklund
Sang Michael Xie
Marvin Zhang
...
A. Kundaje
Emma Pierson
Sergey Levine
Chelsea Finn
Percy Liang
OOD
170
1,428
0
14 Dec 2020
On the Marginal Benefit of Active Learning: Does Self-Supervision Eat
  Its Cake?
On the Marginal Benefit of Active Learning: Does Self-Supervision Eat Its Cake?
Yao-Chun Chan
Mingchen Li
Samet Oymak
SSL
30
23
0
16 Nov 2020
A Survey of Deep Active Learning
A Survey of Deep Active Learning
Pengzhen Ren
Yun Xiao
Xiaojun Chang
Po-Yao (Bernie) Huang
Zhihui Li
Brij B. Gupta
Xiaojiang Chen
Xin Wang
93
1,136
0
30 Aug 2020
Active Crowd Counting with Limited Supervision
Active Crowd Counting with Limited Supervision
Zhen Zhao
Miaojing Shi
Xiaoxiao Zhao
Li Li
46
48
0
13 Jul 2020
Scalable Active Learning for Object Detection
Scalable Active Learning for Object Detection
Elmar Haussmann
Michele Fenzi
Kashyap Chitta
J. Ivanecký
Hanson Xu
D. Roy
Akshita Mittel
Nicolas Koumchatzky
C. Farabet
J. Álvarez
31
109
0
09 Apr 2020
Towards Robust and Reproducible Active Learning Using Neural Networks
Towards Robust and Reproducible Active Learning Using Neural Networks
Prateek Munjal
Nasir Hayat
Munawar Hayat
J. Sourati
Shadab Khan
UQCV
61
69
0
21 Feb 2020
Reinforced active learning for image segmentation
Reinforced active learning for image segmentation
Arantxa Casanova
Pedro H. O. Pinheiro
Negar Rostamzadeh
C. Pal
37
108
0
16 Feb 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library
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
401
42,299
0
03 Dec 2019
Deep Active Learning: Unified and Principled Method for Query and
  Training
Deep Active Learning: Unified and Principled Method for Query and Training
Changjian Shui
Fan Zhou
Christian Gagné
Boyu Wang
FedML
59
153
0
20 Nov 2019
A Survey on Active Learning and Human-in-the-Loop Deep Learning for
  Medical Image Analysis
A Survey on Active Learning and Human-in-the-Loop Deep Learning for Medical Image Analysis
Samuel Budd
E. C. Robinson
Bernhard Kainz
LM&MA
52
477
0
07 Oct 2019
Epistemic Uncertainty Sampling
Epistemic Uncertainty Sampling
Vu-Linh Nguyen
Sebastien Destercke
Eyke Hüllermeier
PER
UD
53
49
0
31 Aug 2019
Bayesian Batch Active Learning as Sparse Subset Approximation
Bayesian Batch Active Learning as Sparse Subset Approximation
Robert Pinsler
Jonathan Gordon
Eric T. Nalisnick
José Miguel Hernández-Lobato
UQCV
47
132
0
06 Aug 2019
Discriminative Active Learning
Discriminative Active Learning
Daniel Gissin
Shai Shalev-Shwartz
47
178
0
15 Jul 2019
BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian
  Active Learning
BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning
Andreas Kirsch
Joost R. van Amersfoort
Y. Gal
FedML
85
627
0
19 Jun 2019
Batch Active Learning Using Determinantal Point Processes
Batch Active Learning Using Determinantal Point Processes
Erdem Biyik
Kenneth Wang
Nima Anari
Dorsa Sadigh
57
62
0
19 Jun 2019
Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds
Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds
Jordan T. Ash
Chicheng Zhang
A. Krishnamurthy
John Langford
Alekh Agarwal
BDL
UQCV
85
772
0
09 Jun 2019
Learning Loss for Active Learning
Learning Loss for Active Learning
Donggeun Yoo
In So Kweon
UQCV
85
661
0
09 May 2019
Bayesian Generative Active Deep Learning
Bayesian Generative Active Deep Learning
Toan M. Tran
Thanh-Toan Do
Ian Reid
G. Carneiro
87
136
0
26 Apr 2019
Variational Adversarial Active Learning
Variational Adversarial Active Learning
Samarth Sinha
Sayna Ebrahimi
Trevor Darrell
GAN
DRL
VLM
SSL
112
579
0
31 Mar 2019
Using Pre-Training Can Improve Model Robustness and Uncertainty
Using Pre-Training Can Improve Model Robustness and Uncertainty
Dan Hendrycks
Kimin Lee
Mantas Mazeika
NoLa
69
726
0
28 Jan 2019
Diverse mini-batch Active Learning
Diverse mini-batch Active Learning
Fedor Zhdanov
55
155
0
17 Jan 2019
Adversarial Active Learning for Deep Networks: a Margin Based Approach
Adversarial Active Learning for Deep Networks: a Margin Based Approach
Mélanie Ducoffe
F. Precioso
GAN
AAML
134
274
0
27 Feb 2018
Deep Active Learning over the Long Tail
Deep Active Learning over the Long Tail
Yonatan Geifman
Ran El-Yaniv
3DPC
65
143
0
02 Nov 2017
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning
  Algorithms
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
Han Xiao
Kashif Rasul
Roland Vollgraf
260
8,876
0
25 Aug 2017
Deep Active Learning for Named Entity Recognition
Deep Active Learning for Named Entity Recognition
Yanyao Shen
Hyokun Yun
Zachary Chase Lipton
Y. Kronrod
Anima Anandkumar
HAI
83
457
0
19 Jul 2017
Deep Bayesian Active Learning with Image Data
Deep Bayesian Active Learning with Image Data
Y. Gal
Riashat Islam
Zoubin Ghahramani
BDL
UQCV
68
1,732
0
08 Mar 2017
Billion-scale similarity search with GPUs
Billion-scale similarity search with GPUs
Jeff Johnson
Matthijs Douze
Hervé Jégou
246
3,717
0
28 Feb 2017
Generative Adversarial Active Learning
Generative Adversarial Active Learning
Jia Jie Zhu
José Bento
GAN
47
185
0
25 Feb 2017
Cost-Effective Active Learning for Deep Image Classification
Cost-Effective Active Learning for Deep Image Classification
Keze Wang
Dongyu Zhang
Ya Li
Ruimao Zhang
Liang Lin
VLM
88
677
0
13 Jan 2017
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp
  Minima
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima
N. Keskar
Dheevatsa Mudigere
J. Nocedal
M. Smelyanskiy
P. T. P. Tang
ODL
415
2,935
0
15 Sep 2016
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
517
5,893
0
08 Jul 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.1K
193,814
0
10 Dec 2015
Bayesian Active Learning for Classification and Preference Learning
Bayesian Active Learning for Classification and Preference Learning
N. Houlsby
Ferenc Huszár
Zoubin Ghahramani
M. Lengyel
110
910
0
24 Dec 2011
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