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Michael Boratko
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2020 – today
- 2022
- [c16]Siddhartha Mishra, Nicholas Monath, Michael Boratko, Ariel Kobren, Andrew McCallum:
An Evaluative Measure of Clustering Methods Incorporating Hyperparameter Sensitivity. AAAI 2022: 7788-7796 - [c15]Shib Sankar Dasgupta, Michael Boratko, Siddhartha Mishra, Shriya Atmakuri, Dhruvesh Patel, Xiang Li, Andrew McCallum:
Word2Box: Capturing Set-Theoretic Semantics of Words using Box Embeddings. ACL (1) 2022: 2263-2276 - [c14]Dhruvesh Patel, Pavitra Dangati, Jay-Yoon Lee, Michael Boratko, Andrew McCallum:
Modeling Label Space Interactions in Multi-label Classification using Box Embeddings. ICLR 2022 - [c13]Dongxu Zhang, Michael Boratko, Cameron Musco, Andrew McCallum:
Modeling Transitivity and Cyclicity in Directed Graphs via Binary Code Box Embeddings. NeurIPS 2022 - 2021
- [c12]Yasumasa Onoe, Michael Boratko, Andrew McCallum, Greg Durrett:
Modeling Fine-Grained Entity Types with Box Embeddings. ACL/IJCNLP (1) 2021: 2051-2064 - [c11]Tejas Chheda, Purujit Goyal, Trang Tran
, Dhruvesh Patel, Michael Boratko, Shib Sankar Dasgupta, Andrew McCallum:
Box Embeddings: An open-source library for representation learning using geometric structures. EMNLP (Demos) 2021: 203-211 - [c10]Xuelu Chen, Michael Boratko, Muhao Chen, Shib Sankar Dasgupta, Xiang Lorraine Li, Andrew McCallum:
Probabilistic Box Embeddings for Uncertain Knowledge Graph Reasoning. NAACL-HLT 2021: 882-893 - [c9]Michael Boratko, Dongxu Zhang, Nicholas Monath, Luke Vilnis, Kenneth L. Clarkson, Andrew McCallum:
Capacity and Bias of Learned Geometric Embeddings for Directed Graphs. NeurIPS 2021: 16423-16436 - [c8]Shib Sankar Dasgupta, Xiang Lorraine Li, Michael Boratko, Dongxu Zhang, Andrew McCallum:
Box-To-Box Transformations for Modeling Joint Hierarchies. RepL4NLP@ACL-IJCNLP 2021: 277-288 - [c7]Michael Boratko, Javier Burroni, Shib Sankar Dasgupta, Andrew McCallum:
Min/max stability and box distributions. UAI 2021: 2146-2155 - [i7]Yasumasa Onoe, Michael Boratko, Greg Durrett:
Modeling Fine-Grained Entity Types with Box Embeddings. CoRR abs/2101.00345 (2021) - [i6]Xuelu Chen, Michael Boratko, Muhao Chen, Shib Sankar Dasgupta, Xiang Lorraine Li, Andrew McCallum:
Probabilistic Box Embeddings for Uncertain Knowledge Graph Reasoning. CoRR abs/2104.04597 (2021) - [i5]Shib Sankar Dasgupta, Michael Boratko, Shriya Atmakuri, Xiang Lorraine Li, Dhruvesh Patel, Andrew McCallum:
Word2Box: Learning Word Representation Using Box Embeddings. CoRR abs/2106.14361 (2021) - [i4]Tejas Chheda, Purujit Goyal, Trang Tran, Dhruvesh Patel, Michael Boratko, Shib Sankar Dasgupta, Andrew McCallum:
Box Embeddings: An open-source library for representation learning using geometric structures. CoRR abs/2109.04997 (2021) - 2020
- [c6]Dhruvesh Patel, Shib Sankar Dasgupta, Michael Boratko, Xiang Li, Luke Vilnis, Andrew McCallum:
Representing Joint Hierarchies with Box Embeddings. AKBC 2020 - [c5]Michael Boratko, Xiang Li, Tim O'Gorman, Rajarshi Das, Dan Le, Andrew McCallum:
ProtoQA: A Question Answering Dataset for Prototypical Common-Sense Reasoning. EMNLP (1) 2020: 1122-1136 - [c4]Shib Sankar Dasgupta, Michael Boratko, Dongxu Zhang, Luke Vilnis, Xiang Li, Andrew McCallum:
Improving Local Identifiability in Probabilistic Box Embeddings. NeurIPS 2020 - [i3]Michael Boratko, Xiang Lorraine Li, Rajarshi Das, Tim O'Gorman, Dan Le, Andrew McCallum:
ProtoQA: A Question Answering Dataset for Prototypical Common-Sense Reasoning. CoRR abs/2005.00771 (2020) - [i2]Shib Sankar Dasgupta, Michael Boratko, Dongxu Zhang, Luke Vilnis, Xiang Lorraine Li, Andrew McCallum:
Improving Local Identifiability in Probabilistic Box Embeddings. CoRR abs/2010.04831 (2020)
2010 – 2019
- 2019
- [c3]Xiang Li, Luke Vilnis, Dongxu Zhang, Michael Boratko, Andrew McCallum:
Smoothing the Geometry of Probabilistic Box Embeddings. ICLR 2019 - 2018
- [c2]Michael Boratko, Harshit Padigela, Divyendra Mikkilineni, Pritish Yuvraj, Rajarshi Das, Andrew McCallum, Maria Chang, Achille Fokoue-Nkoutche, Pavan Kapanipathi, Nicholas Mattei, Ryan Musa, Kartik Talamadupula, Michael Witbrock:
A Systematic Classification of Knowledge, Reasoning, and Context within the ARC Dataset. QA@ACL 2018: 60-70 - [c1]Michael Boratko, Harshit Padigela, Divyendra Mikkilineni, Pritish Yuvraj, Rajarshi Das, Andrew McCallum, Maria Chang, Achille Fokoue, Pavan Kapanipathi, Nicholas Mattei, Ryan Musa, Kartik Talamadupula, Michael Witbrock:
An Interface for Annotating Science Questions. EMNLP (Demonstration) 2018: 102-107 - [i1]Michael Boratko, Harshit Padigela, Divyendra Mikkilineni, Pritish Yuvraj, Rajarshi Das, Andrew McCallum, Maria Chang, Achille Fokoue-Nkoutche, Pavan Kapanipathi, Nicholas Mattei, Ryan Musa, Kartik Talamadupula, Michael Witbrock:
A Systematic Classification of Knowledge, Reasoning, and Context within the ARC Dataset. CoRR abs/1806.00358 (2018)
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last updated on 2023-05-13 03:59 CEST by the dblp team
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