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Comparing the Value of Labeled and Unlabeled Data in Method-of-Moments
  Latent Variable Estimation

Comparing the Value of Labeled and Unlabeled Data in Method-of-Moments Latent Variable Estimation

3 March 2021
Mayee F. Chen
Benjamin Cohen-Wang
Stephen Mussmann
Frederic Sala
Christopher Ré
ArXiv (abs)PDFHTML

Papers citing "Comparing the Value of Labeled and Unlabeled Data in Method-of-Moments Latent Variable Estimation"

7 / 7 papers shown
Title
Empirical Analysis for Unsupervised Universal Dependency Parse Tree
  Aggregation
Empirical Analysis for Unsupervised Universal Dependency Parse Tree Aggregation
Adithya Kulkarni
Oliver Eulenstein
Qi Li
60
0
0
28 Mar 2024
Losses over Labels: Weakly Supervised Learning via Direct Loss
  Construction
Losses over Labels: Weakly Supervised Learning via Direct Loss Construction
Dylan Sam
J. Zico Kolter
NoLaOffRL
134
13
0
13 Dec 2022
Shoring Up the Foundations: Fusing Model Embeddings and Weak Supervision
Shoring Up the Foundations: Fusing Model Embeddings and Weak Supervision
Mayee F. Chen
Daniel Y. Fu
Dyah Adila
Michael Zhang
Frederic Sala
Kayvon Fatahalian
Christopher Ré
66
20
0
24 Mar 2022
Generative Modeling Helps Weak Supervision (and Vice Versa)
Generative Modeling Helps Weak Supervision (and Vice Versa)
Benedikt Boecking
Nicholas Roberts
Willie Neiswanger
Stefano Ermon
Frederic Sala
Artur Dubrawski
50
1
0
22 Mar 2022
Data Consistency for Weakly Supervised Learning
Data Consistency for Weakly Supervised Learning
Chidubem Arachie
Bert Huang
NoLa
70
2
0
08 Feb 2022
Universalizing Weak Supervision
Universalizing Weak Supervision
Changho Shin
Winfred Li
Harit Vishwakarma
Nicholas Roberts
Frederic Sala
NoLa
69
31
0
07 Dec 2021
End-to-End Weak Supervision
End-to-End Weak Supervision
Salva Rühling Cachay
Benedikt Boecking
A. Dubrawski
NoLa
72
41
0
05 Jul 2021
1