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Constrained Labeling for Weakly Supervised Learning

Sep 15, 2020
Chidubem Arachie, Bert Huang


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Woodbury Transformations for Deep Generative Flows

Feb 27, 2020
You Lu, Bert Huang


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Active Learning by Greedy Split and Label Exploration

Jun 17, 2019
Alyssa Herbst, Bert Huang


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Labeled Graph Generative Adversarial Networks

Jun 07, 2019
Shuangfei Fan, Bert Huang


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An Adaptable Framework for Deep Adversarial Label Learning from Weak Supervision

Jun 03, 2019
Chidubem Arachie, Bert Huang


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Structured Output Learning with Conditional Generative Flows

May 30, 2019
You Lu, Bert Huang

* Under Submission 

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Block Belief Propagation for Parameter Learning in Markov Random Fields

Nov 09, 2018
You Lu, Zhiyuan Liu, Bert Huang

* Accepted to AAAI 2019 

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Adversarial Labeling for Learning without Labels

Jun 07, 2018
Chidubem Arachie, Bert Huang


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Best-Choice Edge Grafting for Efficient Structure Learning of Markov Random Fields

May 20, 2018
Walid Chaabene, Bert Huang


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New Fairness Metrics for Recommendation that Embrace Differences

Dec 13, 2017
Sirui Yao, Bert Huang

* Presented as a poster at the 2017 Workshop on Fairness, Accountability, and Transparency in Machine Learning (FAT/ML 2017) 

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Beyond Parity: Fairness Objectives for Collaborative Filtering

Nov 30, 2017
Sirui Yao, Bert Huang


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Hinge-Loss Markov Random Fields and Probabilistic Soft Logic

Nov 17, 2017
Stephen H. Bach, Matthias Broecheler, Bert Huang, Lise Getoor

* Journal of Machine Learning Research (JMLR), 18(109):1-67, 2017 

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Recurrent Collective Classification

Mar 19, 2017
Shuangfei Fan, Bert Huang


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Cyberbullying Identification Using Participant-Vocabulary Consistency

Jun 26, 2016
Elaheh Raisi, Bert Huang

* presented at 2016 ICML Workshop on #Data4Good: Machine Learning in Social Good Applications, New York, NY 

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Hinge-loss Markov Random Fields: Convex Inference for Structured Prediction

Sep 26, 2013
Stephen Bach, Bert Huang, Ben London, Lise Getoor

* Appears in Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI2013) 

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A Hypergraph-Partitioned Vertex Programming Approach for Large-scale Consensus Optimization

Aug 30, 2013
Hui Miao, Xiangyang Liu, Bert Huang, Lise Getoor


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Graph-based Generalization Bounds for Learning Binary Relations

May 31, 2013
Ben London, Bert Huang, Lise Getoor


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Multi-relational Learning Using Weighted Tensor Decomposition with Modular Loss

May 31, 2013
Ben London, Theodoros Rekatsinas, Bert Huang, Lise Getoor


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Approximating the Permanent with Belief Propagation

Aug 12, 2009
Bert Huang, Tony Jebara


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