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biquality-learn: a Python library for Biquality Learning
18 August 2023
Pierre Nodet
V. Lemaire
A. Bondu
Antoine Cornuéjols
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Papers citing
"biquality-learn: a Python library for Biquality Learning"
10 / 10 papers shown
Title
Machine Learning Operations (MLOps): Overview, Definition, and Architecture
Dominik Kreuzberger
Niklas Kühl
Sebastian Hirschl
VLM
AI4CE
31
344
0
04 May 2022
ADAPT : Awesome Domain Adaptation Python Toolbox
Antoine de Mathelin
Mounir Atiq
Guillaume Richard
Alejandro de la Concha
Mouad Yachouti
Franccois Deheeger
Mathilde Mougeot
Nicolas Vayatis
TTA
35
47
0
07 Jul 2021
From Weakly Supervised Learning to Biquality Learning: an Introduction
Pierre Nodet
V. Lemaire
A. Bondu
Antoine Cornuéjols
A. Ouorou
39
22
0
16 Dec 2020
Importance Reweighting for Biquality Learning
Pierre Nodet
V. Lemaire
A. Bondu
Antoine Cornuéjols
NoLa
35
6
0
19 Oct 2020
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
133
14,883
0
18 Jun 2020
Part-dependent Label Noise: Towards Instance-dependent Label Noise
Xiaobo Xia
Tongliang Liu
Bo Han
Nannan Wang
Biwei Huang
Haifeng Liu
Gang Niu
Dacheng Tao
Masashi Sugiyama
NoLa
39
67
0
14 Jun 2020
Rethinking Importance Weighting for Deep Learning under Distribution Shift
Tongtong Fang
Nan Lu
Gang Niu
Masashi Sugiyama
48
139
0
08 Jun 2020
Snorkel: Rapid Training Data Creation with Weak Supervision
Alexander Ratner
Stephen H. Bach
Henry R. Ehrenberg
Jason Alan Fries
Sen Wu
Christopher Ré
73
1,024
0
28 Nov 2017
Learning with Symmetric Label Noise: The Importance of Being Unhinged
Brendan van Rooyen
A. Menon
Robert C. Williamson
NoLa
150
311
0
28 May 2015
Frustratingly Easy Domain Adaptation
Hal Daumé
117
1,799
0
10 Jul 2009
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