Alex Ratner
TitleCited byYear
Data programming: Creating large training sets, quickly
AJ Ratner, CM De Sa, S Wu, D Selsam, C Ré
Advances in neural information processing systems, 3567-3575, 2016
1972016
Snorkel: Rapid training data creation with weak supervision
A Ratner, SH Bach, H Ehrenberg, J Fries, S Wu, C Ré
Proceedings of the VLDB Endowment 11 (3), 269-282, 2017
1472017
Learning to compose domain-specific transformations for data augmentation
AJ Ratner, H Ehrenberg, Z Hussain, J Dunnmon, C Ré
Advances in neural information processing systems, 3236-3246, 2017
822017
Learning the structure of generative models without labeled data
SH Bach, B He, A Ratner, C Ré
Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017
452017
Deepdive: Declarative knowledge base construction
C De Sa, A Ratner, C Ré, J Shin, F Wang, S Wu, C Zhang
ACM SIGMOD Record 45 (1), 60-67, 2016
382016
DeepDive: declarative knowledge base construction
C Zhang, C Ré, M Cafarella, C De Sa, A Ratner, J Shin, F Wang, S Wu
Communications of the ACM 60 (5), 93-102, 2017
292017
Snorkel: Fast training set generation for information extraction
AJ Ratner, SH Bach, HR Ehrenberg, C Ré
Proceedings of the 2017 ACM International Conference on Management of Data …, 2017
262017
Swellshark: A generative model for biomedical named entity recognition without labeled data
J Fries, S Wu, A Ratner, C Ré
arXiv preprint arXiv:1704.06360, 2017
182017
Training complex models with multi-task weak supervision
A Ratner, B Hancock, J Dunnmon, F Sala, S Pandey, C Ré
Proceedings of the AAAI Conference on Artificial Intelligence 33, 4763-4771, 2019
162019
Data programming with ddlite: Putting humans in a different part of the loop
HR Ehrenberg, J Shin, AJ Ratner, JA Fries, C Ré
Proceedings of the Workshop on Human-In-the-Loop Data Analytics, 13, 2016
162016
Snorkel drybell: A case study in deploying weak supervision at industrial scale
SH Bach, D Rodriguez, Y Liu, C Luo, H Shao, C Xia, S Sen, A Ratner, ...
Proceedings of the 2019 International Conference on Management of Data, 362-375, 2019
142019
Incremental knowledge base construction using DeepDive
C Sa, A Ratner, C Ré, J Shin, F Wang, S Wu, C Zhang
The VLDB Journal—The International Journal on Very Large Data Bases 26 (1 …, 2017
142017
Snorkel metal: Weak supervision for multi-task learning
A Ratner, B Hancock, J Dunnmon, R Goldman, C Ré
Proceedings of the Second Workshop on Data Management for End-To-End Machine …, 2018
122018
A kernel theory of modern data augmentation
T Dao, A Gu, AJ Ratner, V Smith, C De Sa, C Ré
Proceedings of machine learning research 97, 1528, 2019
102019
Learning Dependency Structures for Weak Supervision Models
P Varma, F Sala, A He, A Ratner, C Ré
arXiv preprint arXiv:1903.05844, 2019
72019
The Role of Massively Multi-Task and Weak Supervision in Software 2.0.
AJ Ratner, B Hancock, C Ré
CIDR, 2019
62019
Weak Supervision: The New Programming Paradigm for Machine Learning
A Ratner, S Bach, P Varma, C Ré
Jul, 2017
62017
AMELIE accelerates Mendelian patient diagnosis directly from the primary literature
J Birgmeier, M Haeussler, CA Deisseroth, KA Jagadeesh, AJ Ratner, ...
bioRxiv, 171322, 2017
52017
SysML: The New Frontier of Machine Learning Systems
A Ratner, D Alistarh, G Alonso, P Bailis, S Bird, N Carlini, B Catanzaro, ...
arXiv preprint arXiv:1904.03257, 2019
42019
Cross-Modal Data Programming Enables Rapid Medical Machine Learning
J Dunnmon, A Ratner, N Khandwala, K Saab, M Markert, H Sagreiya, ...
arXiv preprint arXiv:1903.11101, 2019
42019
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