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Active One-shot Learning

Active One-shot Learning

21 February 2017
Mark P. Woodward
Chelsea Finn
    VLM
    OffRL
ArXivPDFHTML

Papers citing "Active One-shot Learning"

19 / 19 papers shown
Title
Guided Transfer Learning
Guided Transfer Learning
Danilo Nikolić
Davor Andrić
V. Nikolić
24
2
0
26 Mar 2023
Active learning for data streams: a survey
Active learning for data streams: a survey
Davide Cacciarelli
M. Kulahci
28
40
0
17 Feb 2023
Active Transfer Prototypical Network: An Efficient Labeling Algorithm
  for Time-Series Data
Active Transfer Prototypical Network: An Efficient Labeling Algorithm for Time-Series Data
Yuqi Zhu
M. Tnani
Timo Jahnz
Klaus Diepold
13
0
0
28 Sep 2022
A Comprehensive Survey of Few-shot Learning: Evolution, Applications,
  Challenges, and Opportunities
A Comprehensive Survey of Few-shot Learning: Evolution, Applications, Challenges, and Opportunities
Yisheng Song
Ting-Yuan Wang
S. Mondal
J. P. Sahoo
SLR
52
344
0
13 May 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
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
Low Budget Active Learning via Wasserstein Distance: An Integer
  Programming Approach
Low Budget Active Learning via Wasserstein Distance: An Integer Programming Approach
Rafid Mahmood
Sanja Fidler
M. Law
24
37
0
05 Jun 2021
MedSelect: Selective Labeling for Medical Image Classification Combining
  Meta-Learning with Deep Reinforcement Learning
MedSelect: Selective Labeling for Medical Image Classification Combining Meta-Learning with Deep Reinforcement Learning
Akshay Smit
Damir Vrabac
Yujie He
A. Ng
Andrew L. Beam
Pranav Rajpurkar
16
7
0
26 Mar 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
Contextual Diversity for Active Learning
Contextual Diversity for Active Learning
Sharat Agarwal
H. Arora
Saket Anand
Chetan Arora
26
162
0
13 Aug 2020
MetAL: Active Semi-Supervised Learning on Graphs via Meta Learning
MetAL: Active Semi-Supervised Learning on Graphs via Meta Learning
Kaushalya Madhawa
T. Murata
AI4CE
32
8
0
22 Jul 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
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
Generative One-Shot Learning (GOL): A Semi-Parametric Approach to
  One-Shot Learning in Autonomous Vision
Generative One-Shot Learning (GOL): A Semi-Parametric Approach to One-Shot Learning in Autonomous Vision
Sorin Grigorescu
GAN
VLM
17
12
0
19 Dec 2018
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
27
33
0
09 Oct 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
Putting a bug in ML: The moth olfactory network learns to read MNIST
Putting a bug in ML: The moth olfactory network learns to read MNIST
Charles B. Delahunt
J. Nathan Kutz
24
31
0
15 Feb 2018
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