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AnchorAL: Computationally Efficient Active Learning for Large and
  Imbalanced Datasets
v1v2 (latest)

AnchorAL: Computationally Efficient Active Learning for Large and Imbalanced Datasets

8 April 2024
Pietro Lesci
Andreas Vlachos
ArXiv (abs)PDFHTML

Papers citing "AnchorAL: Computationally Efficient Active Learning for Large and Imbalanced Datasets"

28 / 28 papers shown
Title
On the Limitations of Simulating Active Learning
On the Limitations of Simulating Active Learning
Katerina Margatina
Nikolaos Aletras
82
11
0
21 May 2023
Bag of Tricks for In-Distribution Calibration of Pretrained Transformers
Bag of Tricks for In-Distribution Calibration of Pretrained Transformers
Jaeyoung Kim
Dongbin Na
Sungchul Choi
Sungbin Lim
VLM
74
5
0
13 Feb 2023
Whose Language Counts as High Quality? Measuring Language Ideologies in
  Text Data Selection
Whose Language Counts as High Quality? Measuring Language Ideologies in Text Data Selection
Suchin Gururangan
Dallas Card
Sarah K. Drier
E. K. Gade
Leroy Z. Wang
Zeyu Wang
Luke Zettlemoyer
Noah A. Smith
259
81
0
25 Jan 2022
Influence-Balanced Loss for Imbalanced Visual Classification
Influence-Balanced Loss for Imbalanced Visual Classification
Seulki Park
Jongin Lim
Younghan Jeon
J. Choi
CVBM
128
136
0
06 Oct 2021
Active Learning by Acquiring Contrastive Examples
Active Learning by Acquiring Contrastive Examples
Katerina Margatina
Giorgos Vernikos
Loïc Barrault
Nikolaos Aletras
83
193
0
08 Sep 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
64
156
0
29 Jul 2021
Deduplicating Training Data Makes Language Models Better
Deduplicating Training Data Makes Language Models Better
Katherine Lee
Daphne Ippolito
A. Nystrom
Chiyuan Zhang
Douglas Eck
Chris Callison-Burch
Nicholas Carlini
SyDa
360
636
0
14 Jul 2021
Revisiting Uncertainty-based Query Strategies for Active Learning with
  Transformers
Revisiting Uncertainty-based Query Strategies for Active Learning with Transformers
Christopher Schröder
A. Niekler
Martin Potthast
65
81
0
12 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
55
106
0
01 Jul 2021
On the Importance of Effectively Adapting Pretrained Language Models for
  Active Learning
On the Importance of Effectively Adapting Pretrained Language Models for Active Learning
Katerina Margatina
Loïc Barrault
Nikolaos Aletras
60
38
0
16 Apr 2021
Fine-tuning BERT for Low-Resource Natural Language Understanding via
  Active Learning
Fine-tuning BERT for Low-Resource Natural Language Understanding via Active Learning
Daniel Grießhaber
J. Maucher
Ngoc Thang Vu
72
46
0
04 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
186
184
0
19 Oct 2020
Array Programming with NumPy
Array Programming with NumPy
Charles R. Harris
K. Millman
S. Walt
R. Gommers
Pauli Virtanen
...
Tyler Reddy
Warren Weckesser
Hameer Abbasi
C. Gohlke
T. Oliphant
156
15,026
0
18 Jun 2020
MPNet: Masked and Permuted Pre-training for Language Understanding
MPNet: Masked and Permuted Pre-training for Language Understanding
Kaitao Song
Xu Tan
Tao Qin
Jianfeng Lu
Tie-Yan Liu
109
1,138
0
20 Apr 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
556
42,639
0
03 Dec 2019
Exploring the Limits of Transfer Learning with a Unified Text-to-Text
  Transformer
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Colin Raffel
Noam M. Shazeer
Adam Roberts
Katherine Lee
Sharan Narang
Michael Matena
Yanqi Zhou
Wei Li
Peter J. Liu
AIMat
495
20,342
0
23 Oct 2019
ALBERT: A Lite BERT for Self-supervised Learning of Language
  Representations
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
Zhenzhong Lan
Mingda Chen
Sebastian Goodman
Kevin Gimpel
Piyush Sharma
Radu Soricut
SSLAIMat
373
6,469
0
26 Sep 2019
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
Nils Reimers
Iryna Gurevych
1.3K
12,316
0
27 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
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
89
629
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
BDLUQCV
105
777
0
09 Jun 2019
Learning Loss for Active Learning
Learning Loss for Active Learning
Donggeun Yoo
In So Kweon
UQCV
85
663
0
09 May 2019
Adversarial Sampling for Active Learning
Adversarial Sampling for Active Learning
Christoph Mayer
Radu Timofte
GAN
131
117
0
20 Aug 2018
A Closer Look at Memorization in Deep Networks
A Closer Look at Memorization in Deep Networks
Devansh Arpit
Stanislaw Jastrzebski
Nicolas Ballas
David M. Krueger
Emmanuel Bengio
...
Tegan Maharaj
Asja Fischer
Aaron Courville
Yoshua Bengio
Simon Lacoste-Julien
TDI
131
1,829
0
16 Jun 2017
Billion-scale similarity search with GPUs
Billion-scale similarity search with GPUs
Jeff Johnson
Matthijs Douze
Hervé Jégou
257
3,741
0
28 Feb 2017
Bayesian Optimal Active Search and Surveying
Bayesian Optimal Active Search and Surveying
Roman Garnett
Yamuna Krishnamurthy
Xuehan Xiong
J. Schneider
R. Mann
66
115
0
27 Jun 2012
SMOTE: Synthetic Minority Over-sampling Technique
SMOTE: Synthetic Minority Over-sampling Technique
Nitesh Chawla
Kevin W. Bowyer
Lawrence Hall
W. Kegelmeyer
AI4TS
388
25,747
0
09 Jun 2011
Rates of convergence in active learning
Rates of convergence in active learning
Steve Hanneke
135
154
0
09 Mar 2011
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