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Ke Zhai 0001

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affiliation: Microsoft AI & Research, Sunnyvale, CA, USA
affiliation (former): Yahoo!, Sunnyvale, CA, USA
affiliation (PhD): University of Maryland, College Park, MD, USA

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2010 – 2019

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2018
[c8]
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  - electronic edition @ openreview.net (open access)
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Ke Zhai, Huan Wang:
Adaptive Dropout with Rademacher Complexity Regularization. ICLR (Poster) 2018
2016
[c7]
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  - conf/acl/KozarevaLZG16
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Zornitsa Kozareva, Qi Li, Ke Zhai, Weiwei Guo:
Recognizing Salient Entities in Shopping Queries. ACL (2) 2016
[c6]
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  - conf/sigir/ZhaiKHLG16
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Ke Zhai, Zornitsa Kozareva, Yuening Hu, Qi Li, Weiwei Guo:
Query to Knowledge: Unsupervised Entity Extraction from Shopping Queries using Adaptor Grammars. SIGIR 2016: 255-264
2014
[b1]
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Ke Zhai:
Models, Inference, and Implementation for Scalable Probabilistic Models of Text. University of Maryland, College Park, MD, USA, 2014
[j1]
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Ke Zhai, Jordan L. Boyd-Graber, Shay B. Cohen:
Online Adaptor Grammars with Hybrid Inference. Trans. Assoc. Comput. Linguistics 2: 465-476 (2014)
[c5]
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Ke Zhai, Jason D. Williams:
Discovering Latent Structure in Task-Oriented Dialogues. ACL (1) 2014: 36-46
[c4]
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Yuening Hu, Ke Zhai, Vladimir Eidelman, Jordan L. Boyd-Graber:
Polylingual Tree-Based Topic Models for Translation Domain Adaptation. ACL (1) 2014: 1166-1176
2013
[c3]
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Ke Zhai, Jordan L. Boyd-Graber:
Online Latent Dirichlet Allocation with Infinite Vocabulary. ICML (1) 2013: 561-569
2012
[c2]
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Ke Zhai, Yuening Hu, Jordan L. Boyd-Graber, Sinead Williamson:
Modeling Images using Transformed Indian Buffet Processes. ICML 2012
[c1]
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Ke Zhai, Jordan L. Boyd-Graber, Nima Asadi, Mohamad L. Alkhouja:
Mr. LDA: a flexible large scale topic modeling package using variational inference in MapReduce. WWW 2012: 879-888
2011
[i1]
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  - journals/corr/abs-1107-3765
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Ke Zhai, Jordan L. Boyd-Graber, Nima Asadi:
Using Variational Inference and MapReduce to Scale Topic Modeling. CoRR abs/1107.3765 (2011)

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