Heng-Tze Cheng is a technical lead manager and staff software engineer at Google
Research. Heng-Tze founded the Wide & Deep Learning project in TensorFlow, and has
worked on large-scale machine learning platforms that are widely used for retrieval,
ranking, and recommender systems. Prior to joining Google in 2014, Heng-Tze received
his Ph.D. from Carnegie Mellon University in 2013 and B.S. from National Taiwan
University in 2008. His research interests range across machine learning, information
retrieval, user behavior modeling, and human activity recognition.
Google Publications
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TFX: A TensorFlow-Based Production-Scale Machine
Learning Platform
Akshay Naresh Modi, Chiu Yuen Koo, Chuan Yu Foo, Clemens Mewald, Denis M. Baylor,
Eric Breck, Heng-Tze Cheng, Jarek Wilkiewicz, Levent Koc,
Lukasz Lew, Martin A. Zinkevich, Martin
Wicke, Mustafa Ispir, Neoklis
Polyzotis, Noah Fiedel, Salem Elie Haykal, Steven Whang, Sudip
Roy, Sukriti Ramesh, Vihan Jain, Xin Zhang, Zakaria Haque
KDD 2017
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TensorFlow Estimators: Managing Simplicity vs.
Flexibility in High-Level Machine Learning Frameworks
Cassandra Xia, Clemens Mewald, D. Sculley,
David Soergel, George Roumpos, Heng-Tze Cheng, Illia Polosukhin, Jamie Alexander Smith, Jianwei
Xie, Lichan Hong, Martin Wicke, Mustafa
Ispir, Philip Daniel Tucker, Yuan Tang, Zakaria Haque
Proceedings of the 23th ACM SIGKDD International Conference on Knowledge
Discovery and Data Mining, Halifax, Canada (2017)
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Wide & Deep Learning for Recommender Systems
Heng-Tze Cheng, Levent Koc, Jeremiah Harmsen, Tal Shaked, Tushar Chandra, Hrishi Aradhye, Glen Anderson, Greg Corrado, Wei Chai, Mustafa Ispir, Rohan Anil,
Zakaria Haque, Lichan Hong, Vihan Jain, Xiaobing
Liu, Hemal Shah
arXiv:1606.07792 (2016)
Previous Publications
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Nonparametric Discovery of Human Routine from Sensor Data
Feng-Tso Sun, Yi-Ting Yeh, Heng-Tze Cheng,
Cynthia Kuo, Martin Griss
IEEE International Conference on Pervasive Computing and Communications (PerCom)
(2014)
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NuActiv: Recognizing Unseen New Activities Using Semantic Attribute-Based
Learning
Heng-Tze Cheng, Feng-Tso Sun, Martin
Griss, Paul Davis, Jianguo Li, Di You
Proceeding of the 11th Annual International Conference on Mobile Systems,
Applications, and Services, ACM, New York, NY, USA (2013), pp. 361-374
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Towards zero-shot learning for human activity recognition using semantic
attribute sequence model
Heng-Tze Cheng, Martin Griss, Paul Davis,
Jianguo Li, Di You
UbiComp '13 Proceedings of the 2013 ACM international joint conference on
Pervasive and ubiquitous computing, ACM
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SensOrchestra: Collaborative Sensing for Symbolic Location Recognition
Heng-Tze Cheng, Feng-Tso Sun, Senaka
Buthpitiya, Martin Griss
International Conference on Mobile Computing, Applications, and Services, 2010
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Automatic Chord Recognition for Music Classification and Retrieval
Heng-Tze Cheng, Yi-Hsuan Yang, Yu-Ching
Lin, I-Bin Liao, Homer H. Chen
IEEE International Conference on Multimedia and Expo (ICME), 2008
