Learning Dependency Structures for Weak Supervision Models

14 March 2019

Alexander Ratner

Papers citing "Learning Dependency Structures for Weak Supervision Models"

20 / 20 papers shown

Title
An Adaptive Method for Weak Supervision with Drifting Data Alessio Mazzetto Reza Esfandiarpoor E. Upfal Stephen H. Bach Stephen H. Bach 120 1 0 02 Jun 2023
Language Models Enable Simple Systems for Generating Structured Views of Heterogeneous Data Lakes Simran Arora Brandon Yang Sabri Eyuboglu A. Narayan Andrew Hojel Immanuel Trummer Christopher Ré SyDa 107 79 0 19 Apr 2023
Multi-Resolution Weak Supervision for Sequential Data Frederic Sala P. Varma Jason Alan Fries Daniel Y. Fu Shiori Sagawa ... A. Ramamoorthy K. Xiao Kayvon Fatahalian J. Priest Christopher Ré NoLa 146 29 0 21 Oct 2019
Training Complex Models with Multi-Task Weak Supervision Alexander Ratner Braden Hancock Jared A. Dunnmon Frederic Sala Shreyash Pandey Christopher Ré 53 213 0 05 Oct 2018
Inferring Generative Model Structure with Static Analysis P. Varma Bryan D. He Payal Bajaj Imon Banerjee Nishith Khandwala D. Rubin Christopher Ré 61 58 0 07 Sep 2017
Learning the Structure of Generative Models without Labeled Data Stephen H. Bach Bryan D. He Alexander Ratner Christopher Ré 65 166 0 02 Mar 2017
Socratic Learning: Augmenting Generative Models to Incorporate Latent Subsets in Training Data P. Varma Bryan D. He Dan Iter Peng Xu Rose Yu Christopher De Sa Christopher Ré 80 27 0 25 Oct 2016
Data Programming: Creating Large Training Sets, Quickly Alexander Ratner Christopher De Sa Sen Wu Daniel Selsam Christopher Ré 197 718 0 25 May 2016
Incremental Knowledge Base Construction Using DeepDive Jaeho Shin Sen Wu Feiran Wang Christopher De Sa Ce Zhang Christopher Ré CLL HAI 166 290 0 03 Feb 2015
On the Information Theoretic Limits of Learning Ising Models Karthikeyan Shanmugam Rashish Tandon A. Dimakis Pradeep Ravikumar 63 36 0 05 Nov 2014
Spectral Methods meet EM: A Provably Optimal Algorithm for Crowdsourcing Yuchen Zhang Xi Chen Dengyong Zhou Michael I. Jordan FedML 152 386 0 15 Jun 2014
Learning Latent Variable Gaussian Graphical Models Zhaoshi Meng Brian Eriksson Alfred Hero 274 41 0 10 Jun 2014
On the sample covariance matrix estimator of reduced effective rank population matrices, with applications to fPCA F. Bunea Luo Xiao 666 92 0 21 Dec 2012
Structure estimation for discrete graphical models: Generalized covariance matrices and their inverses Po-Ling Loh Martin J. Wainwright 86 180 0 03 Dec 2012
High-dimensional covariance matrix estimation with missing observations Karim Lounici 188 183 0 12 Jan 2012
$High-dimensional Ising model selection using ${\ell_1}$-regularized logistic regression$ High-dimensional Ising model selection using ${\ell_1}$ -regularized logistic regression Pradeep Ravikumar Martin J. Wainwright John D. Lafferty 280 956 0 02 Oct 2010
Latent variable graphical model selection via convex optimization V. Chandrasekaran P. Parrilo A. Willsky CML 209 509 0 06 Aug 2010
Rank-Sparsity Incoherence for Matrix Decomposition V. Chandrasekaran Sujay Sanghavi P. Parrilo A. Willsky CML 257 1,111 0 11 Jun 2009
Information-theoretic limits of selecting binary graphical models in high dimensions N. Santhanam Martin J. Wainwright 146 204 0 16 May 2009
$High-dimensional covariance estimation by minimizing $\ell_1$-penalized log-determinant divergence$ High-dimensional covariance estimation by minimizing $\ell_1$ -penalized log-determinant divergence Pradeep Ravikumar Martin J. Wainwright Garvesh Raskutti Bin Yu 249 873 0 21 Nov 2008