Machine Learning Department, School of Computer Science, Carnegie Mellon University, PA

Transcription

1 Pengtao Xie Carnegie Mellon University Machine Learning Department School of Computer Science 5000 Forbes Ave Pittsburgh, PA Tel: (412) Web: pengtaox Research Interests Latent variable models Large scale distributed machine learning Education Machine Learning Department, School of Computer Science, Carnegie Mellon University, PA PhD student in Machine Learning, May 2015 Language Technologies Institute, School of Computer Science, Carnegie Mellon University, PA Master s student in Language Technologies, August 2013 May Department of Computer Science and Technology, Tsinghua University, Beijing, China M.E. in Computer Science, September 2010 July Advisor: Prof. Mingsheng Ying College of Computer Science, Sichuan University, Chengdu, China B.E. in Computer Science, September 2006 July Publications Refereed Conference Papers Pengtao Xie, Jun Zhu, and Eric P. Xing. Diversity-Promoting Bayesian Learning of Latent Variable Models. International Conference on Machine Learning. (ICML 2016) Oral presentation. Pengtao Xie, Jin Kyu Kim, Yi Zhou, Qirong Ho, Abhimanu Kumar, Yaoliang Yu and Eric P. Xing. Lighter- Communication Distributed Machine Learning via Sufficient Factor Broadcasting. Conference on Uncertainty in Artificial Intelligence. (UAI 2016). Eric P. Xing, Qirong Ho, Wei Dai, Jin Kyu Kim, Jinliang Wei, Seunghak Lee, Xun Zheng, Pengtao Xie, Abhimanu Kumar, and Yaoliang Yu. Petuum: A new Platform for Distributed Machine Learning on Big Data. IEEE Transactions on Big Data. (TBD 2015).

2 Pengtao Xie 2 Pengtao Xie. Learning Compact and Effective Distance Metrics with Diversity Regularization. In European Conference on Machine Learning. (ECML 2015) Oral presentation. Pengtao Xie, Yuntian Deng, and Eric Xing. Diversifying Restricted Boltzmann Machine for Document Modeling. In ACM SIGKDD Conference on Knowledge Discovery and Data Mining. (KDD 2015) Oral presentation. Eric P. Xing, Qirong Ho, Wei Dai, Jin Kyu Kim, Jinliang Wei, Seunghak Lee, Xun Zheng, Pengtao Xie, Abhimanu Kumar, and Yaoliang Yu. Petuum: A new Platform for Distributed Machine Learning on Big Data. In ACM SIGKDD Conference on Knowledge Discovery and Data Mining. (KDD 2015) Oral presentation. Pengtao Xie, Diyi Yang and Eric P. Xing. Incorporating Word Correlation Knowledge into Topic Modeling. In Conference of the North American Chapter of the Association for Computational Linguistics. (NAACL 2015). Pengtao Xie, Yulong Pei, Yuan Xie and Eric P. Xing. Mining User Interests from Personal Photos. In Proceedings of the 29th AAAI Conference on Artificial Intelligence. (AAAI 2015). Pengtao Xie and Eric P. Xing. Integrating Image Clustering and Codebook Learning. In Proceedings of the 29th AAAI Conference on Artificial Intelligence. (AAAI 2015) Oral presentation. Pengtao Xie and Eric P. Xing. Integrating Document Clustering and Topic Modeling. In Proceedings of the 29th International Conference on Uncertainty in Artificial Intelligence. (UAI 2013). Pengtao Xie and Eric P. Xing. Multi-Modal Distance Metric Learning. In 23rd International Joint Conference on Artificial Intelligence. (IJCAI 2013) Oral presentation. Research Experience Microsoft Research, Redmond, WA Research intern in Cloud Machine Learning Team and Machine Learning Group, May 2014 Aug Mentors: Dr. Thomas Finley, Dr. Misha Bilenko, Dr. Ran Gilad-Bachrach Language Technologies Institute, Carnegie Mellon University, PA Master s student in Language Technologies, August 2013 present. Machine Learning Department, Carnegie Mellon University, PA Visiting student in SAILING Lab, September 2011 July Robotics Institute, Carnegie Mellon University, PA Visiting student in Human Sensing Lab, May 2011 September Advisor: Prof. Fernando De la Torre Microsoft Research Asia, Beijing, China Research intern in Web Search and Mining group, August 2009 June Mentor: Dr. Rong Xiao

3 Pengtao Xie 3 Sichuan University, Chengdu, China Research Assistant in Machine Intelligence Lab, February 2009 July Advisor: Prof. Jiancheng Lv Teaching Experience Teaching Assistant in Carnegie Mellon University, Pittsburgh, PA 10708, Probabilistic Graphical Models. Instructor: Prof. Eric Xing, Spring , Machine Learning. Instructors: Prof. Barnabas Poczos and Prof. Aarti Singh, Spring , Machine Learning. Instructors: Prof. William Cohen and Prof. Eric Xing, Fall Professional Activities Program Committee Member for Asian Conference on Computer Vision (ACCV), 2016 Reviewer for European Conference on Computer Vision (ECCV), 2016 Program Committee Member for Annual Meeting of the Association for Computational Linguistics (ACL), 2016 Program Committee Member for IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Reviewer for Journal of the American Statistical Association (JASA). Program Committee Member for Annual Meeting of the Association for Computational Linguistics (ACL), Reviewer for Conference on Empirical Methods in Natural Language Processing (EMNLP), 2015 Reviewer for International Conference on Computer Vision (ICCV), 2015 Reviewer for ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2015 Reviewer for International Conference on Machine Learning (ICML), Reviewer for IEEE Transactions on Knowledge and Data Engineering (TKDE). Reviewer for IEEE Transactions on Neural Networks and Learning Systems (TNNLS). Membership: ACM, IEEE. Talks Database Seminar, Carnegie Mellon University, Mar Sufficient Factor Broadcasting for Distributed Machine Learning. 11th CSL Student Conference, University of Illinois Urbana-Champaign, Feb Latent Variable Modeling with Diversity-Inducing Mutual Angular Regularization. Artificial Intelligence Seminar, Carnegie Mellon University, Feb Diversity-Inducing Learning of Latent Variable Models: Frequentist and Bayesian Perspectives.

4 Pengtao Xie 4 VALSE Webinar, Oct Diversity Regularization of Latent Variable Models: Theory, Algorithm and Applications. Machine Learning Lunch Seminar, Carnegie Mellon University, Sept Mutual Angular Regularization of Latent Variable Models: Thoery, Algorithm and Applications. Beihang University, Aug Diversifying Restricted Boltzmann Machine for Document Modeling. ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Sydney, Aug Diversifying Restricted Boltzmann Machine for Document Modeling. VASC Seminar, Carnegie Mellon University, April Integrating Image Clustering and Codebook Learning. Machine Learning Lunch Seminar, Carnegie Mellon University, April Integrating Data Clustering and Representation Learning. SCS Student Seminar, Carnegie Mellon University, April Incorporating Word Correlation Knowledge into Topic Modeling. CL+NLP Seminar, Carnegie Mellon University, Apr Incorporating Word Correlation Knowledge into Topic Modeling. Database Seminar, Carnegie Mellon University, Mar Mining User Interests from Personal Photos. 29th AAAI Conference on Artificial Intelligence, Austin, Jan Integrating Image Clustering and Codebook Learning. Database Seminar, Carnegie Mellon University, Sep CryptGraph: Privacy Preserving Graph Analytics on Encrypted Graph. Machine Learning Lunch Seminar, Carnegie Mellon University, Sep Privacy Preserving Neural Network Prediction on Encrypted Data. Cylab Student Seminar, Carnegie Mellon University, Sep Privacy-Preserving Neural Network Prediction on Encrypted Data. SDI/ISTC Seminar, Carnegie Mellon University and Intel, Sep Privacy-Preserving Neural Network Prediction on Encrypted Data. Cloud Machine Learning Team and Machine Learning Group, Microsoft Research, Aug Privacy-Preserving Neural Network Prediction on Encrypted Data. Cryptography Group, Microsoft Research, Jul Privacy-Preserving Neural Network Prediction on Encrypted Data. 23rd International Joint Conference on Artificial Intelligence (IJCAI 2013), Beijing, Aug Multi-Modal Distance Metric Learning. Awards and Honors KDD Travel Award, Siebel Scholarship, Excellent Master Graduate Award, Dept of CS, Tsinghua University, UAI 2013 Travel Scholarship, 2013.

5 Pengtao Xie 5 Excellent Bachelor Thesis Award, Excellent Bachelor Graduate Award, National Scholarship of China, First Class Sichuan University Scholarship, Sichuan University Excellent Student, Second Prize in Challenge Cup Technological Invention Competition, Third Prize in National English Contest for College Students, Successful Winner in Microsoft Imagine Cup Software Design Competition, Creative Talented Student Award granted by Sichuan University, Sichuan University Excellent Student Leader, National First Prize in China Undergraduate Mathematical Contest of Modeling, Gold Prize in Challenge Cup Entrepreneurship Contest of Sichuan Province, First Prize in Challenge Cup Entrepreneurship Contest of Sichuan University, Goldman Sachs Global Leader Scholarship, National Excitation Scholarship, Sichuan University Excellent Student Leader, 2007.