We stand with Ukraine  

Ke Zhai

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


According to our database1, Ke Zhai authored at least 11 papers between 2011 and 2018.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2018
Adaptive Dropout with Rademacher Complexity Regularization.
[BibTeX]
[DOI]
Ke Zhai
,
Huan Wang
Proceedings of the 6th International Conference on Learning Representations, 2018

2016
Query to Knowledge: Unsupervised Entity Extraction from Shopping Queries using Adaptor Grammars.
[BibTeX]
[DOI]
Ke Zhai
,
Zornitsa Kozareva
,
Yuening Hu
,
Qi Li
,
Weiwei Guo
Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval, 2016

Recognizing Salient Entities in Shopping Queries.
[BibTeX]
[DOI]
Zornitsa Kozareva
,
Qi Li
,
Ke Zhai
,
Weiwei Guo
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016

2014
Models, Inference, and Implementation for Scalable Probabilistic Models of Text.
[BibTeX]
[DOI]
Ke Zhai
PhD thesis, 2014

Online Adaptor Grammars with Hybrid Inference.
[BibTeX]
[DOI]
Ke Zhai
,
Jordan L. Boyd-Graber
,
Shay B. Cohen
Trans. Assoc. Comput. Linguistics, 2014

Discovering Latent Structure in Task-Oriented Dialogues.
[BibTeX]
[DOI]
Ke Zhai
,
Jason D. Williams
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, 2014

Polylingual Tree-Based Topic Models for Translation Domain Adaptation.
[BibTeX]
[DOI]
Yuening Hu
,
Ke Zhai
,
Vladimir Eidelman
,
Jordan L. Boyd-Graber
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, 2014

2013
Online Latent Dirichlet Allocation with Infinite Vocabulary.
[BibTeX]
[DOI]
Ke Zhai
,
Jordan L. Boyd-Graber
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
Mr. LDA: a flexible large scale topic modeling package using variational inference in MapReduce.
[BibTeX]
[DOI]
Ke Zhai
,
Jordan L. Boyd-Graber
,
Nima Asadi
,
Mohamad L. Alkhouja
Proceedings of the 21st World Wide Web Conference 2012, 2012

Modeling Images using Transformed Indian Buffet Processes.
[BibTeX]
[DOI]
Ke Zhai
,
Yuening Hu
,
Jordan L. Boyd-Graber
,
Sinead Williamson
Proceedings of the 29th International Conference on Machine Learning, 2012

2011
Using Variational Inference and MapReduce to Scale Topic Modeling
[BibTeX]
[DOI]
Ke Zhai
,
Jordan L. Boyd-Graber
,
Nima Asadi
CoRR, 2011


  Loading...