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2020 – today
- 2023
[i11]Luis Oala, Manil Maskey, Lilith Bat-Leah, Alicia Parrish, Nezihe Merve Gürel, Tzu-Sheng Kuo, Yang Liu, Rotem Dror, Danilo Brajovic, Xiaozhe Yao, Max Bartolo, William Gaviria Rojas, Ryan Hileman, Rainier Aliment, Michael W. Mahoney, Meg Risdal, Matthew Lease, Wojciech Samek, Debojyoti Dutta, Curtis G. Northcutt, Cody Coleman, Braden Hancock, Bernard Koch, Girmaw Abebe Tadesse, Bojan Karlas, Ahmed M. Alaa, Adji Bousso Dieng, Natasha F. Noy, Vijay Janapa Reddi, James Zou, Praveen K. Paritosh, Mihaela van der Schaar, Kurt D. Bollacker, Lora Aroyo, Ce Zhang, Joaquin Vanschoren, Isabelle Guyon, Peter Mattson:
DMLR: Data-centric Machine Learning Research - Past, Present and Future. CoRR abs/2311.13028 (2023)- 2022
- [i10]Ryan Smith, Jason A. Fries, Braden Hancock, Stephen H. Bach:
Language Models in the Loop: Incorporating Prompting into Weak Supervision. CoRR abs/2205.02318 (2022)
2010 – 2019
- 2019
- [b1]Braden Hancock:
Weak supervision from high-level abstractions. Stanford University, USA, 2019 - [c10]Alexander Ratner, Braden Hancock, Jared Dunnmon, Frederic Sala, Shreyash Pandey, Christopher Ré:
Training Complex Models with Multi-Task Weak Supervision. AAAI 2019: 4763-4771 - [c9]Braden Hancock, Antoine Bordes, Pierre-Emmanuel Mazaré, Jason Weston:
Learning from Dialogue after Deployment: Feed Yourself, Chatbot! ACL (1) 2019: 3667-3684 - [c8]Alexander J. Ratner, Braden Hancock, Christopher Ré:
The Role of Massively Multi-Task and Weak Supervision in Software 2.0. CIDR 2019 - [c7]Stephen H. Bach, Daniel Rodriguez, Yintao Liu, Chong Luo, Haidong Shao, Cassandra Xia, Souvik Sen, Alexander Ratner, Braden Hancock, Houman Alborzi, Rahul Kuchhal, Christopher Ré, Rob Malkin:
Snorkel DryBell: A Case Study in Deploying Weak Supervision at Industrial Scale. SIGMOD Conference 2019: 362-375 - [c6]Braden Hancock, Hongrae Lee, Cong Yu:
Generating Titles for Web Tables. WWW 2019: 638-647 - [i9]Braden Hancock, Antoine Bordes, Pierre-Emmanuel Mazaré, Jason Weston:
Learning from Dialogue after Deployment: Feed Yourself, Chatbot! CoRR abs/1901.05415 (2019) - 2018
- [c5]Braden Hancock, Paroma Varma, Stephanie Wang, Martin Bringmann, Percy Liang, Christopher Ré:
Training Classifiers with Natural Language Explanations. ACL (1) 2018: 1884-1895 - [c4]Alexander Ratner, Braden Hancock, Jared Dunnmon, Roger E. Goldman, Christopher Ré:
Snorkel MeTaL: Weak Supervision for Multi-Task Learning. DEEM@SIGMOD 2018: 3:1-3:4 - [c3]Sen Wu, Luke Hsiao, Xiao Cheng, Braden Hancock, Theodoros Rekatsinas
, Philip Alexander Levis, Christopher Ré:
Fonduer: Knowledge Base Construction from Richly Formatted Data. SIGMOD Conference 2018: 1301-1316 - [i8]Braden Hancock, Paroma Varma, Stephanie Wang, Martin Bringmann, Percy Liang, Christopher Ré:
Training Classifiers with Natural Language Explanations. CoRR abs/1805.03818 (2018) - [i7]Braden Hancock, Hongrae Lee, Cong Yu:
Title Generation for Web Tables. CoRR abs/1807.00099 (2018) - [i6]Alexander Ratner, Braden Hancock, Jared Dunnmon, Frederic Sala, Shreyash Pandey, Christopher Ré:
Training Complex Models with Multi-Task Weak Supervision. CoRR abs/1810.02840 (2018) - [i5]Stephen H. Bach, Daniel Rodriguez, Yintao Liu, Chong Luo, Haidong Shao, Cassandra Xia, Souvik Sen, Alexander Ratner, Braden Hancock, Houman Alborzi, Rahul Kuchhal, Christopher Ré, Rob Malkin:
Snorkel DryBell: A Case Study in Deploying Weak Supervision at Industrial Scale. CoRR abs/1812.00417 (2018) - 2017
- [i4]Sen Wu, Luke Hsiao, Xiao Cheng, Braden Hancock, Theodoros Rekatsinas, Philip Alexander Levis, Christopher Ré:
Fonduer: Knowledge Base Construction from Richly Formatted Data. CoRR abs/1703.05028 (2017) - 2016
- [c2]Adrian Benton, Michael J. Paul, Braden Hancock, Mark Dredze:
Collective Supervision of Topic Models for Predicting Surveys with Social Media. AAAI 2016: 2892-2898 - [i3]Adrian Benton, Braden Hancock, Glen Coppersmith, John W. Ayers, Mark Dredze:
After Sandy Hook Elementary: A Year in the Gun Control Debate on Twitter. CoRR abs/1610.02060 (2016) - 2015
- [c1]Jeremy Kepner, Vijay Gadepally, Braden Hancock, Peter Michaleas, Elizabeth Michel, Mayank Varia:
Parallel vectorized algebraic AES in Matlab for rapid prototyping of encrypted sensor processing algorithms and database analytics. HPEC 2015: 1-8 - [i2]Vijay Gadepally, Braden Hancock, Benjamin Kaiser, Jeremy Kepner, Peter Michaleas, Mayank Varia, Arkady Yerukhimovich:
Computing on Masked Data to improve the Security of Big Data. CoRR abs/1504.01287 (2015) - [i1]Jeremy Kepner, Vijay Gadepally, Braden Hancock, Peter Michaleas, Elizabeth Michel, Mayank Varia:
Parallel Vectorized Algebraic AES in MATLAB for Rapid Prototyping of Encrypted Sensor Processing Algorithms and Database Analytics. CoRR abs/1506.08503 (2015)
Coauthor Index
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