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Our goal is to enable machine learning systems to be trained interactively.
An experimental time-sharing system
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Learning from labeled and unlabeled data with label propagation
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Graphical models, exponential families, and variational inference
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Modeling annotators: A generative approach to learning from annotator rationales
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Imagenet: A large-scale hierarchical image database
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Probabilistic graphical models: principles and techniques
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Learning from measurements in exponential families
Percy Liang, Michael I Jordan, and Dan Klein · 2009
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Distant supervision for relation extraction without labeled data
Mike Mintz, Steven Bills, Rion Snow, and Dan Jurafsky · 2009
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Generalized expectation criteria for semi-supervised learning with weakly labeled data
Gideon S Mann and Andrew McCallum · 2010
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Knowledge-based weak supervision for information extraction of overlapping relations
Raphael Hoffmann, Congle Zhang, Xiao Ling, Luke Zettlemoyer, and Daniel S Weld · 2011
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Iterative learning for reliable crowdsourcing systems
David R Karger, Sewoong Oh, and Devavrat Shah · 2011
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Deepdive: Web-scale knowledge-base construction using statistical learning and inference
Feng Niu, Ce Zhang, Christopher Ré, and Jude W Shavlik · 2012
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Reducing wrong labels in distant supervision for relation extraction
Shingo Takamatsu, Issei Sato, and Hiroshi Nakagawa · 2012
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Improved pattern learning for bootstrapped entity extraction
Sonal Gupta and Christopher Manning · 2014
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Tubespam: Comment spam filtering on youtube
Túlio C Alberto, Johannes V Lochter, and Tiago A Almeida · 2015
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Activitynet: A large-scale video benchmark for human activity understanding
Fabian Caba Heilbron, Victor Escorcia, Bernard Ghanem, and Juan Carlos Niebles · 2015
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Information preserving dimensionality reduction
Shrinu Kushagra and Shai Ben-David · 2015
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Imagenet large scale visual recognition challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, et al · 2015
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What do a million news articles look like?
David Corney, Dyaa Albakour, Miguel Martinez-Alvarez, and Samir Moussa · 2016
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Learning visual features from large weakly supervised data
Armand Joulin, Laurens van der Maaten, Allan Jabri, and Nicolas Vasilache · 2016
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Data programming: Creating large training sets, quickly
A. J. Ratner, Christopher M. De Sa, Sen Wu, Daniel Selsam, and C. Ré · 2016
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Yfcc100m: The new data in multimedia research
Bart Thomee, David A Shamma, Gerald Friedland, Benjamin Elizalde, Karl Ni, Douglas Poland, Damian Borth, and Li-Jia Li · 2016
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Matching networks for one shot learning
Oriol Vinyals, Charles Blundell, Timothy Lillicrap, Daan Wierstra, et al · 2016
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Learning the structure of generative models without labeled data
Stephen H Bach, Bryan He, Alexander Ratner, and Christopher Ré · 2017
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Learning to learn from weak supervision by full supervision
Mostafa Dehghani, Aliaksei Severyn, Sascha Rothe, and Jaap Kamps · 2017
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Neural ranking models with weak supervision
Mostafa Dehghani, Hamed Zamani, Aliaksei Severyn, Jaap Kamps, and W Bruce Croft · 2017
Unified language model pre-training for natural language understanding and generation
Li Dong, Nan Yang, Wenhui Wang, Furu Wei, Xiaodong Liu, Yu Wang, Jianfeng Gao, Ming Zhou, and Hsiao-Wuen Hon · 2019
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Weakly supervised classification of aortic valve malformations using unlabeled cardiac mri sequences
Jason Fries, Paroma Varma, Vincent S Chen, Ke Xiao, Heliodoro Tejeda, Priyanka Saha, Jared Dunnmon, Henry Chubb, Shiraz Maskatia, Madalina Fiterau, et al · 2019
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Rekall: Specifying video events using compositions of spatiotemporal labels
Daniel Y. Fu, Will Crichton, James Hong, Xinwei Yao, Haotian Zhang, Anh Truong, Avanika Narayan, Maneesh Agrawala, Christopher Ré, and Kayvon Fatahalian · 2019
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Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2019
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Label propagation for deep semi-supervised learning
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Constrained deep weak supervision for histopathology image segmentation
Zhipeng Jia, Xingyi Huang, I Eric, Chao Chang, and Yan Xu · 2017
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Learning visual n-grams from web data
Ang Li, Allan Jabri, Armand Joulin, and Laurens van der Maaten · 2017
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Prototypical networks for few-shot learning
Jake Snell, Kevin Swersky, and Richard Zemel · 2017
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Revisiting unreasonable effectiveness of data in deep learning era
Chen Sun, Abhinav Shrivastava, Saurabh Singh, and Abhinav Gupta · 2017
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DeepDive: Declarative knowledge base construction
Ce Zhang, Christopher Ré, Michael Cafarella, Christopher De Sa, Alex Ratner, Jaeho Shin, Feiran Wang, and Sen Wu · 2017
Cited alongside, same era.
https://archive.org/details/tv, 2018
Internet archive: Tv news archive · 2018
Cited alongside, same era.
Ahmet Iscen, Giorgos Tolias, Yannis Avrithis, and Ondrej Chum · 2019
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Generalization through memorization: Nearest neighbor language models
Urvashi Khandelwal, Omer Levy, Dan Jurafsky, Luke Zettlemoyer, and Mike Lewis · 2019
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Large scale learning of general visual representations for transfer
Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Joan Puigcerver, Jessica Yung, Sylvain Gelly, and Neil Houlsby · 2019
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Albert: A lite bert for self-supervised learning of language representations
Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, and Radu Soricut · 2019
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Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever · 2019
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu · 2019
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Training complex models with multi-task weak supervision
A. J. Ratner, B. Hancock, J. Dunnmon, F. Sala, S. Pandey, and C. Ré · 2019
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Multi-resolution weak supervision for sequential data
Frederic Sala, Paroma Varma, Jason Fries, Daniel Y. Fu, Shiori Sagawa, Saelig Khattar, Ashwini Ramamoorthy, Ke Xiao, Kayvon Fatahalian, James Priest, and Christopher Ré · 2019
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Learning dependency structures for weak supervision models
P. Varma, F. Sala, A. He, A. J. Ratner, and C. Ré · 2019
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Huggingface’s transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, R’emi Louf, Morgan Funtowicz, and Jamie Brew · 2019
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Xlnet: Generalized autoregressive pretraining for language understanding
Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Russ R Salakhutdinov, and Quoc V Le · 2019
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Generating multi-agent trajectories using programmatic weak supervision
Eric Zhan, Stephan Zheng, Yisong Yue, Long Sha, and Patrick Lucey · 2019
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Language models are few-shot learners
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei · 2020
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Fast and three-rious: Speeding up weak supervision with triplet methods
Daniel Y. Fu, Mayee F. Chen, Frederic Sala, Sarah M. Hooper, Kayvon Fatahalian, and Christopher Ré · 2020
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Overton: A data system for monitoring and improving machine-learned products
Christopher Ré, Feng Niu, Pallavi Gudipati, and Charles Srisuwananukorn · 2020
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Weak supervision as an efficient approach for automated seizure detection in electroencephalography
Khaled Saab, Jared Dunnmon, Christopher Ré, Daniel Rubin, and Christopher Lee-Messer · 2020
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Weakly supervised sequence tagging from noisy rules
Esteban Safranchik, Shiying Luo, and Stephen H Bach · 2020
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Migrating a privacy-safe information extraction system to a software 2.0 design
Ying Sheng, Nguyen Ha Vo, James B. Wendt, Sandeep Tata, and Marc Najork · 2020
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Learning with weak supervision for email intent detection
Kai Shu, Subhabrata (Subho) Mukherjee, Guoqing Zheng, Ahmed Hassan Awadallah, Milad Shokouhi, and Susan Dumais · 2020
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