Braden Hancock
Braden Hancock
Co-Founder & Head of Technology, Snorkel AI
Verified email at - Homepage
Cited by
Cited by
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 (01), 4763-4771, 2019
Learning from dialogue after deployment: Feed yourself, chatbot!
B Hancock, A Bordes, PE Mazare, J Weston
arXiv preprint arXiv:1901.05415, 2019
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
Training classifiers with natural language explanations
B Hancock, M Bringmann, P Varma, P Liang, S Wang, C Ré
Proceedings of the conference. Association for Computational Linguistics …, 2018
Fonduer: Knowledge base construction from richly formatted data
S Wu, L Hsiao, X Cheng, B Hancock, T Rekatsinas, P Levis, C Ré
Proceedings of the 2018 international conference on management of data, 1301 …, 2018
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
A Machine-Compiled Database of Genome-Wide Association Studies
V Kuleshov, J Ding, B Hancock, A Ratner, C Ré, S Batzoglou, M Snyder
Bio-Ontologies 2017, 2017
After Sandy Hook Elementary: A year in the gun control debate on Twitter
A Benton, B Hancock, G Coppersmith, JW Ayers, M Dredze
arXiv preprint arXiv:1610.02060, 2016
The Smart Normal Constraint Method for Directly Generating a Smart Pareto Set
BJ Hancock, CA Mattson
Structural and Multidisciplinary Optimization, 1-13, 2013
The Role of Massively Multi-Task and Weak Supervision in Software 2.0.
AJ Ratner, B Hancock, C Ré
CIDR, 2019
Recommender Systems for the Department of Defense and Intelligence Community
V Gadepally, B Hancock, K Greenfield, J Campbell, W Campbell, ...
The Lincoln Laboratory Journal 22 (1), 74-89, 2016
Collective supervision of topic models for predicting surveys with social media
A Benton, M Paul, B Hancock, M Dredze
Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016
Computing on masked data to improve the security of big data
V Gadepally, B Hancock, B Kaiser, J Kepner, P Michaleas, M Varia, ...
2015 IEEE International Symposium on Technologies for Homeland Security (HST …, 2015
Generating titles for web tables
B Hancock, H Lee, C Yu
The World Wide Web Conference, 638-647, 2019
Language models in the loop: Incorporating prompting into weak supervision
R Smith, JA Fries, B Hancock, SH Bach
arXiv preprint arXiv:2205.02318, 2022
Reducing shock interactions in transonic turbine via three-dimensional aerodynamic shaping
BJ Hancock, JP Clark
Journal of Propulsion and Power 30 (5), 1248-1256, 2014
Usage scenarios for design space exploration with a dynamic multiobjective optimization formulation
SK Curtis, BJ Hancock, CA Mattson
Research in Engineering Design 24, 395-409, 2013
Somebody's watching: The ever-growing internet of things
B Hancock, LN Hancock
Phi kappa phi forum 96 (3), 13-16, 2016
Divergent exploration in design with a dynamic multiobjective optimization formulation
SK Curtis, CA Mattson, BJ Hancock, PK Lewis
Structural and Multidisciplinary Optimization 47 (5), 645-657, 2012
Parallel vectorized algebraic AES in Matlab for rapid prototyping of encrypted sensor processing algorithms and database analytics
J Kepner, V Gadepally, B Hancock, P Michaleas, E Michel, M Varia
2015 IEEE High Performance Extreme Computing Conference (HPEC), 1-8, 2015
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