Ke Zhai | Staff Research Scientist @ Apple

I am currently a Staff Research Scientist at Apple, focusing on pushing the boundaries of machine learning and its practical applications.

Research Interests

Statistical Machine Learning
Large-scale: Distributed and Online Learning
Probabilistic Bayesian Models

Education

Ph.D. in Computer Science University of Maryland, College Park

Advised by Dr. Jordan Boyd-Graber and co-supervised by Dr. Jimmy Lin. Associated with UMIACS, Cloud Computing Center, and CLIP Lab. Focus: non-parametric Bayesian learning and cloud computing.

M.S. in Computer Science (2011) University of Maryland, College Park Paper: "Using Variational Inference and MapReduce to Scale Topic Models"

B.E. in Computer Engineering (2009) Nanyang Technological University, Singapore Thesis: "An Embedded Caching Framework for Privacy-Preserving Data Mining"

Publications

(* indicates equal contribution)

Adaptive Dropout with Rademacher Complexity Regularization

Ke Zhai*, and Huan Wang*.

International Conference on Learning Representations (ICLR), 2018

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Query to Knowledge: Unsupervised Entity Extraction from Shopping Queries using Adaptor Grammars

Ke Zhai, Zornitsa Kozareva, Yuening Hu, Qi Li and Weiwei Guo.

SIGIR, 2016

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Recognizing Salient Entities in Shopping Queries

Zornitsa Kozareva, Qi Li, Ke Zhai and Weiwei Guo.

ACL, 2016

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Online Adaptor Grammars with Hybrid Inference

Ke Zhai, Jordan Boyd-Graber and Shay B. Cohen.

TACL, 2014

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Discovering Latent Structure in Task-Oriented Dialogues

Ke Zhai and Jason D. Williams.

ACL, 2014

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Polylingual Tree-Based Topic Models for Translation Domain Adaptation

Ke Zhai*, Yuening Hu*, Vladimir Edelman and Jordan Boyd-Graber.

ACL, 2014

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Online Latent Dirichlet Allocation with Infinite Vocabulary

Ke Zhai and Jordan Boyd-Graber.

ICML, 2013

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Modeling Images using Transformed Indian Buffet Processes

Ke Zhai*, Yuening Hu*, Sinead Williamson and Jordan Boyd-Graber.

ICML, 2012

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Mr. LDA: A Flexible Large Scale Topic Modeling Package using Variational Inference in MapReduce

Ke Zhai, Jordan Boyd-Graber, Nima Asadi and Mohamed Alkhouja.

WWW, 2012

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Speeding Up Secure Computations via Embedded Caching

Ke Zhai, Wee Keong Ng, Andre Ricardo Herianto and Shuguo Han.

SDM, 2009

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