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Learning how to Active Learn: A Deep Reinforcement Learning Approach

Learning how to Active Learn: A Deep Reinforcement Learning Approach

8 August 2017
Meng Fang
Yuan Li
Trevor Cohn
ArXivPDFHTML

Papers citing "Learning how to Active Learn: A Deep Reinforcement Learning Approach"

41 / 41 papers shown
Title
Rethinking Epistemic and Aleatoric Uncertainty for Active Open-Set Annotation: An Energy-Based Approach
Rethinking Epistemic and Aleatoric Uncertainty for Active Open-Set Annotation: An Energy-Based Approach
Chen-Chen Zong
Sheng-Jun Huang
EDL
92
0
0
27 Feb 2025
Image Classification with Deep Reinforcement Active Learning
Image Classification with Deep Reinforcement Active Learning
Mingyuan Jiu
Xuguang Song
H. Sahbi
Shupan Li
Yan Chen
Wei Guo
Lihua Guo
Mingliang Xu
VLM
29
0
0
31 Dec 2024
Turn-Level Active Learning for Dialogue State Tracking
Turn-Level Active Learning for Dialogue State Tracking
Zihan Zhang
Meng Fang
Fanghua Ye
Ling-Hao Chen
Mohammad-Reza Namazi-Rad
48
1
0
23 Oct 2023
Active learning for data streams: a survey
Active learning for data streams: a survey
Davide Cacciarelli
M. Kulahci
30
40
0
17 Feb 2023
Active Example Selection for In-Context Learning
Active Example Selection for In-Context Learning
Yiming Zhang
Shi Feng
Chenhao Tan
SILM
LRM
32
187
0
08 Nov 2022
A Survey of Active Learning for Natural Language Processing
A Survey of Active Learning for Natural Language Processing
Zhisong Zhang
Emma Strubell
Eduard H. Hovy
LM&MA
35
65
0
18 Oct 2022
When Bioprocess Engineering Meets Machine Learning: A Survey from the
  Perspective of Automated Bioprocess Development
When Bioprocess Engineering Meets Machine Learning: A Survey from the Perspective of Automated Bioprocess Development
Nghia Duong-Trung
Stefan Born
Jong Woo Kim
M. Schermeyer
Katharina Paulick
...
Thorben Werner
Randolf Scholz
Lars Schmidt-Thieme
Peter Neubauer
Ernesto Martinez
36
20
0
02 Sep 2022
Asking for Knowledge: Training RL Agents to Query External Knowledge
  Using Language
Asking for Knowledge: Training RL Agents to Query External Knowledge Using Language
Iou-Jen Liu
Xingdi Yuan
Marc-Alexandre Côté
Pierre-Yves Oudeyer
Alex Schwing
RALM
21
12
0
12 May 2022
Towards Computationally Feasible Deep Active Learning
Towards Computationally Feasible Deep Active Learning
Akim Tsvigun
Artem Shelmanov
Gleb Kuzmin
Leonid Sanochkin
Daniil Larionov
Gleb Gusev
Manvel Avetisian
L. Zhukov
32
15
0
07 May 2022
Onception: Active Learning with Expert Advice for Real World Machine
  Translation
Onception: Active Learning with Expert Advice for Real World Machine Translation
Vania Mendoncca
Ricardo Rei
Luísa Coheur
Alberto Sardinha INESC-ID Lisboa
38
6
0
09 Mar 2022
Budget-aware Few-shot Learning via Graph Convolutional Network
Budget-aware Few-shot Learning via Graph Convolutional Network
Shipeng Yan
Songyang Zhang
Xuming He
11
6
0
07 Jan 2022
Towards General and Efficient Active Learning
Towards General and Efficient Active Learning
Yichen Xie
Masayoshi Tomizuka
Wei Zhan
VLM
35
10
0
15 Dec 2021
A Framework for Learning to Request Rich and Contextually Useful
  Information from Humans
A Framework for Learning to Request Rich and Contextually Useful Information from Humans
Khanh Nguyen
Yonatan Bisk
Hal Daumé
49
16
0
14 Oct 2021
OPAD: An Optimized Policy-based Active Learning Framework for Document
  Content Analysis
OPAD: An Optimized Policy-based Active Learning Framework for Document Content Analysis
Sumit Shekhar
Bhanu Prakash Reddy Guda
Ashutosh Chaubey
Ishan Jindal
Avanish Jain
33
0
0
01 Oct 2021
Generalization in Text-based Games via Hierarchical Reinforcement
  Learning
Generalization in Text-based Games via Hierarchical Reinforcement Learning
Yunqiu Xu
Meng Fang
Ling Chen
Yali Du
Chengqi Zhang
AI4CE
45
20
0
21 Sep 2021
ProtoInfoMax: Prototypical Networks with Mutual Information Maximization
  for Out-of-Domain Detection
ProtoInfoMax: Prototypical Networks with Mutual Information Maximization for Out-of-Domain Detection
Iftitahu Ni'mah
Meng Fang
Vlado Menkovski
Mykola Pechenizkiy
35
5
0
27 Aug 2021
ImitAL: Learning Active Learning Strategies from Synthetic Data
ImitAL: Learning Active Learning Strategies from Synthetic Data
Julius Gonsior
Maik Thiele
Wolfgang Lehner
23
4
0
17 Aug 2021
Adaptive Selection of Informative Path Planning Strategies via
  Reinforcement Learning
Adaptive Selection of Informative Path Planning Strategies via Reinforcement Learning
Taeyeong Choi
Grzegorz Cielniak
13
10
0
14 Aug 2021
Reinforcement Learning Approach to Active Learning for Image
  Classification
Reinforcement Learning Approach to Active Learning for Image Classification
Thorben Werner
13
1
0
12 Aug 2021
Multi-Domain Active Learning: Literature Review and Comparative Study
Multi-Domain Active Learning: Literature Review and Comparative Study
Ruidan He
Shengcai Liu
Shan He
Ke Tang
OOD
19
14
0
25 Jun 2021
Diminishing Uncertainty within the Training Pool: Active Learning for
  Medical Image Segmentation
Diminishing Uncertainty within the Training Pool: Active Learning for Medical Image Segmentation
V. Nath
Dong Yang
Bennett A. Landman
Daguang Xu
H. Roth
35
68
0
07 Jan 2021
Embodied Visual Active Learning for Semantic Segmentation
Embodied Visual Active Learning for Semantic Segmentation
David Nilsson
Aleksis Pirinen
Erik Gartner
C. Sminchisescu
42
35
0
17 Dec 2020
Cold-start Active Learning through Self-supervised Language Modeling
Cold-start Active Learning through Self-supervised Language Modeling
Michelle Yuan
Hsuan-Tien Lin
Jordan L. Boyd-Graber
116
180
0
19 Oct 2020
Contextual Diversity for Active Learning
Contextual Diversity for Active Learning
Sharat Agarwal
H. Arora
Saket Anand
Chetan Arora
26
162
0
13 Aug 2020
Graph Policy Network for Transferable Active Learning on Graphs
Graph Policy Network for Transferable Active Learning on Graphs
Shengding Hu
Zheng Xiong
Meng Qu
Xingdi Yuan
Marc-Alexandre Côté
Zhiyuan Liu
Jian Tang
GNN
27
65
0
24 Jun 2020
Structure-Level Knowledge Distillation For Multilingual Sequence
  Labeling
Structure-Level Knowledge Distillation For Multilingual Sequence Labeling
Xinyu Wang
Yong-jia Jiang
Nguyen Bach
Tao Wang
Fei Huang
Kewei Tu
30
36
0
08 Apr 2020
Reinforced active learning for image segmentation
Reinforced active learning for image segmentation
Arantxa Casanova
Pedro H. O. Pinheiro
Negar Rostamzadeh
C. Pal
21
108
0
16 Feb 2020
Improving Neural Relation Extraction with Positive and Unlabeled
  Learning
Improving Neural Relation Extraction with Positive and Unlabeled Learning
Zhengqiu He
Wenliang Chen
Yuyi Wang
Wei Zhang
Guanchu Wang
Min Zhang
SSL
AI4TS
20
17
0
28 Nov 2019
Optimizing Data Usage via Differentiable Rewards
Optimizing Data Usage via Differentiable Rewards
Xinyi Wang
Hieu H. Pham
Paul Michel
Antonios Anastasopoulos
J. Carbonell
Graham Neubig
18
60
0
22 Nov 2019
On the Limits of Learning to Actively Learn Semantic Representations
On the Limits of Learning to Actively Learn Semantic Representations
Omri Koshorek
Gabriel Stanovsky
Yichu Zhou
Vivek Srikumar
Jonathan Berant
OffRL
27
9
0
05 Oct 2019
Deep Active Learning with Adaptive Acquisition
Deep Active Learning with Adaptive Acquisition
Manuel Haussmann
Fred Hamprecht
M. Kandemir
22
41
0
27 Jun 2019
Multi-modal Active Learning From Human Data: A Deep Reinforcement
  Learning Approach
Multi-modal Active Learning From Human Data: A Deep Reinforcement Learning Approach
Ognjen Rudovic
Meiru Zhang
Bjorn Schuller
Rosalind W. Picard
OffRL
36
44
0
07 Jun 2019
The Importance of Metric Learning for Robotic Vision: Open Set
  Recognition and Active Learning
The Importance of Metric Learning for Robotic Vision: Open Set Recognition and Active Learning
Benjamin J. Meyer
Tom Drummond
14
33
0
27 Feb 2019
Learning to Learn in Simulation
Learning to Learn in Simulation
Ervin Teng
Bob Iannucci
19
1
0
05 Feb 2019
Large-Scale Visual Active Learning with Deep Probabilistic Ensembles
Large-Scale Visual Active Learning with Deep Probabilistic Ensembles
Kashyap Chitta
J. Álvarez
Adam Lesnikowski
BDL
UQCV
11
34
0
08 Nov 2018
Discovering General-Purpose Active Learning Strategies
Discovering General-Purpose Active Learning Strategies
Ksenia Konyushkova
Raphael Sznitman
Pascal Fua
30
33
0
09 Oct 2018
Visual Curiosity: Learning to Ask Questions to Learn Visual Recognition
Visual Curiosity: Learning to Ask Questions to Learn Visual Recognition
Jianwei Yang
Jiasen Lu
Stefan Lee
Dhruv Batra
Devi Parikh
16
42
0
01 Oct 2018
Leveraging Motion Priors in Videos for Improving Human Segmentation
Leveraging Motion Priors in Videos for Improving Human Segmentation
Yu-Ting Chen
Wen-Yen Chang
Hai Lu
Tingfan Wu
Min Sun
23
2
0
30 Jul 2018
Learning How to Self-Learn: Enhancing Self-Training Using Neural
  Reinforcement Learning
Learning How to Self-Learn: Enhancing Self-Training Using Neural Reinforcement Learning
Chenhua Chen
Yue Zhang
SSL
22
11
0
16 Apr 2018
Deep Reinforcement Learning: An Overview
Deep Reinforcement Learning: An Overview
Yuxi Li
OffRL
VLM
104
1,503
0
25 Jan 2017
Convolutional Neural Networks for Sentence Classification
Convolutional Neural Networks for Sentence Classification
Yoon Kim
AILaw
VLM
309
13,373
0
25 Aug 2014
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