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Ground Truth Inference for Weakly Supervised Entity Matching

Ground Truth Inference for Weakly Supervised Entity Matching

13 November 2022
Renzhi Wu
Alexander Bendeck
Xu Chu
Yeye He
ArXivPDFHTML

Papers citing "Ground Truth Inference for Weakly Supervised Entity Matching"

25 / 25 papers shown
Title
Learning Hyper Label Model for Programmatic Weak Supervision
Learning Hyper Label Model for Programmatic Weak Supervision
Renzhi Wu
Sheng Chen
Jieyu Zhang
Xu Chu
43
17
0
27 Jul 2022
Learning to be a Statistician: Learned Estimator for Number of Distinct
  Values
Learning to be a Statistician: Learned Estimator for Number of Distinct Values
Renzhi Wu
Bolin Ding
Xu Chu
Zhewei Wei
Xiening Dai
Tao Guan
Jingren Zhou
41
12
0
06 Feb 2022
Learning to Solve Hard Minimal Problems
Learning to Solve Hard Minimal Problems
Petr Hrubý
Timothy Duff
A. Leykin
Tomas Pajdla
87
32
0
06 Dec 2021
WRENCH: A Comprehensive Benchmark for Weak Supervision
WRENCH: A Comprehensive Benchmark for Weak Supervision
Jieyu Zhang
Yue Yu
Yinghao Li
Yujing Wang
Yaming Yang
Mao Yang
Alexander Ratner
57
113
0
23 Sep 2021
End-to-End Weak Supervision
End-to-End Weak Supervision
Salva Rühling Cachay
Benedikt Boecking
A. Dubrawski
NoLa
56
41
0
05 Jul 2021
Crowdsourcing via Annotator Co-occurrence Imputation and Provable
  Symmetric Nonnegative Matrix Factorization
Crowdsourcing via Annotator Co-occurrence Imputation and Provable Symmetric Nonnegative Matrix Factorization
Shahana Ibrahim
Xiao Fu
34
9
0
14 Jun 2021
BERTifying the Hidden Markov Model for Multi-Source Weakly Supervised
  Named Entity Recognition
BERTifying the Hidden Markov Model for Multi-Source Weakly Supervised Named Entity Recognition
Yinghao Li
Pranav Shetty
Lu Liu
Chao Zhang
Le Song
NoLa
41
34
0
26 May 2021
Exploiting Transitivity Constraints for Entity Matching in Knowledge
  Graphs
Exploiting Transitivity Constraints for Entity Matching in Knowledge Graphs
J. Baas
Mehdi Dastani
A. Feelders
30
3
0
22 Apr 2021
Apollo: An Adaptive Parameter-wise Diagonal Quasi-Newton Method for
  Nonconvex Stochastic Optimization
Apollo: An Adaptive Parameter-wise Diagonal Quasi-Newton Method for Nonconvex Stochastic Optimization
Xuezhe Ma
ODL
51
31
0
28 Sep 2020
Named Entity Recognition without Labelled Data: A Weak Supervision
  Approach
Named Entity Recognition without Labelled Data: A Weak Supervision Approach
Pierre Lison
A. Hubin
Jeremy Barnes
Samia Touileb
48
113
0
30 Apr 2020
Deep Entity Matching with Pre-Trained Language Models
Deep Entity Matching with Pre-Trained Language Models
Yuliang Li
Jinfeng Li
Yoshihiko Suhara
A. Doan
W. Tan
VLM
70
381
0
01 Apr 2020
Fast and Three-rious: Speeding Up Weak Supervision with Triplet Methods
Fast and Three-rious: Speeding Up Weak Supervision with Triplet Methods
Daniel Y. Fu
Mayee F. Chen
Frederic Sala
Sarah Hooper
Kayvon Fatahalian
Christopher Ré
OffRL
72
115
0
27 Feb 2020
Strength from Weakness: Fast Learning Using Weak Supervision
Strength from Weakness: Fast Learning Using Weak Supervision
Joshua Robinson
Stefanie Jegelka
S. Sra
56
32
0
19 Feb 2020
ZeroER: Entity Resolution using Zero Labeled Examples
ZeroER: Entity Resolution using Zero Labeled Examples
Renzhi Wu
Sanya Chaba
Saurabh Sawlani
Xu Chu
Saravanan Thirumuruganathan
40
91
0
16 Aug 2019
Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning
Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning
Eric Arazo
Diego Ortego
Paul Albert
Noel E. O'Connor
Kevin McGuinness
119
840
0
08 Aug 2019
GOGGLES: Automatic Image Labeling with Affinity Coding
GOGGLES: Automatic Image Labeling with Affinity Coding
Nilaksh Das
Sanya Chaba
Renzhi Wu
Sakshi Gandhi
Duen Horng Chau
Xu Chu
VLM
50
33
0
11 Mar 2019
Training Complex Models with Multi-Task Weak Supervision
Training Complex Models with Multi-Task Weak Supervision
Alexander Ratner
Braden Hancock
Jared A. Dunnmon
Frederic Sala
Shreyash Pandey
Christopher Ré
46
212
0
05 Oct 2018
modAL: A modular active learning framework for Python
modAL: A modular active learning framework for Python
Tivadar Danka
P. Horváth
41
105
0
02 May 2018
Snorkel: Rapid Training Data Creation with Weak Supervision
Snorkel: Rapid Training Data Creation with Weak Supervision
Alexander Ratner
Stephen H. Bach
Henry R. Ehrenberg
Jason Alan Fries
Sen Wu
Christopher Ré
73
1,027
0
28 Nov 2017
PointNet: Deep Learning on Point Sets for 3D Classification and
  Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
C. Qi
Hao Su
Kaichun Mo
Leonidas Guibas
3DH
3DPC
3DV
PINN
474
14,302
0
02 Dec 2016
Data Programming: Creating Large Training Sets, Quickly
Data Programming: Creating Large Training Sets, Quickly
Alexander Ratner
Christopher De Sa
Sen Wu
Daniel Selsam
Christopher Ré
183
716
0
25 May 2016
Incremental Knowledge Base Construction Using DeepDive
Incremental Knowledge Base Construction Using DeepDive
Jaeho Shin
Sen Wu
Feiran Wang
Christopher De Sa
Ce Zhang
Christopher Ré
CLL
HAI
123
290
0
03 Feb 2015
Understanding Random Forests: From Theory to Practice
Understanding Random Forests: From Theory to Practice
Gilles Louppe
101
742
0
28 Jul 2014
SiGMa: Simple Greedy Matching for Aligning Large Knowledge Bases
SiGMa: Simple Greedy Matching for Aligning Large Knowledge Bases
Simon Lacoste-Julien
Konstantina Palla
Alex O. Davies
Gjergji Kasneci
T. Graepel
Zoubin Ghahramani
75
194
0
19 Jul 2012
SMOTE: Synthetic Minority Over-sampling Technique
SMOTE: Synthetic Minority Over-sampling Technique
Nitesh Chawla
Kevin W. Bowyer
Lawrence Hall
W. Kegelmeyer
AI4TS
352
25,621
0
09 Jun 2011
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