Pengtao Xie - Carnegie Mellon School of Computer Science

Pengtao Xie - Carnegie Mellon School of Computer Science

Pengtao Xie Carnegie Mellon University Machine Learning Department School of Computer Science 5000 Forbes Ave Pittsburgh, PA 15213 Tel: (412) 320-623...

79KB Sizes 0 Downloads 0 Views

Recommend Documents

tRuEcasIng - Carnegie Mellon School of Computer Science
Lucian Vlad Lita ♤. Carnegie Mellon [email protected] Abe Ittycheriah. IBM T.J. Watson [email protected] Salim Roukos.

Apparition - Carnegie Mellon School of Computer Science
(4) A to-do list that shows what has been drawn by the user but not yet converted to UI elements. Workers can ... Appari

Print - Carnegie Mellon School of Computer Science
Jan 23, 2014 - primarily Xerox's Palo Alto Research Center in California. Apple co-founder Steve Jobs and his team got m

VCEGAR - Carnegie Mellon School of Computer Science
less scalable. The RTL level of a hardware description language such as ... We describe. a hardware model checking tool,

DiscoTect - Carnegie Mellon School of Computer Science
Architecture Building: We represent architectures us- ing the Acme ..... [20] G.C. Murphy , D. Notkin, Lightweight lexic

Curriculum Vitae - Carnegie Mellon School of Computer Science
Julia Schwarz, Robert Xiao, Jennifer Mankoff, Scott Hudson, Chris Harrison, ..... Sougata Mukherjea, James Foley, Scott

kirthevasan kandasamy - Carnegie Mellon School of Computer Science
party publishers violating Google AdSense policies. Associate Engineer (Intern). Zone24x7. Sri Lanka, Mar-May 2011. Deve

Mitchell et al. - Carnegie Mellon School of Computer Science
May 30, 2008 - Tom M. Mitchell,1* Svetlana V. Shinkareva,2 Andrew Carlson,1 Kai-Min Chang ..... K. Kipper, A. Korhonen,

Jason Wiese - Carnegie Mellon School of Computer Science
Revelle College Provost's Honor List. Minor: Cognitive Science. Visiting Undergraduate 2006-2007. School of Informatics,

1 Introduction - Carnegie Mellon School of Computer Science
Shortcomings of the MUC scorer (Bagga and Baldwin, 1998) ..... (Bhattacharya and Getoor, 2006) Indrajit Bhattacharya and

Pengtao Xie Carnegie Mellon University Machine Learning Department School of Computer Science 5000 Forbes Ave Pittsburgh, PA 15213

Tel: (412) 320-6230 Email: [email protected] Web: http://www.cs.cmu.edu/˜pengtaox

Research Interests Latent space models Machine learning for healthcare Large scale distributed machine learning

Education Carnegie Mellon University, 2013 — 2018 (Expected) PhD student in Machine Learning, M.S in Language Technologies (2015) Advisor: Prof. Eric Xing

Tsinghua University, China, 2010 — 2013 M.E. in Computer Science Advisor: Prof. Mingsheng Ying

Sichuan University, China, 2006 — 2010 B.E. in Computer Science

Publications Pengtao Xie, Barnabas Poczos and Eric P. Xing. Near-Orthogonality Regularization in Kernel Methods. The Conference on Uncertainty in Artificial Intelligence. (UAI 2017) Plenary presentation. Pengtao Xie, Aarti Singh and Eric P. Xing. Uncorrelation and Evenness: A New Diversity-Promoting Regularizer. The 34th International Conference on Machine Learning. (ICML 2017) Oral presentation. Pengtao Xie, Yuntian Deng, Yi Zhou, Abhimanu Kumar, Yaoliang Yu, James Zou and Eric P. Xing. Learning Latent Space Models with Angular Constraints. The 34th International Conference on Machine Learning. (ICML 2017) Oral presentation. Jianxin Li, Haoyi Zhou, Pengtao Xie and Yingchun Zhang. Improving the Generalization Performance of Multiclass SVM via Angular Regularization. The 26th International Joint Conference on Artificial Intelligence. (IJCAI 2017). Pengtao Xie and Eric P. Xing. A Constituent-Centric Neural Architecture for Reading Comprehension. The 55th Annual Meeting of the Association for Computational Linguistics. (ACL 2017).

Pengtao Xie

2

Hao Zhang, Zeyu Zheng, Shizhen Xu, Wei Dai, Qirong Ho, Xiaodan Liang, Zhiting Hu, Jinliang Wei, Pengtao Xie and Eric P. Xing. Poseidon: An Efficient Communication Interface for Distributed Deep Learning on GPU Clusters. 2017 USENIX Annual Technical Conference. (ATC 2017) Oral presentation. Ying Zhou, Xumin Ni, Kai Yuan, Yaoliang Yu, Pengtao Xie, Eric P. Xing and Shuhua Xu. Inference of MultipleWave Population Admixture by Modeling Decay of Linkage Disequilibrium with Polynomial Functions. Heredity 118.May (2017): 503-510. Eric P. Xing, Qirong Ho, Pengtao Xie and Wei Dai. Strategies and Principles of Distributed Machine Learning on Big Data. Engineering, Transactions of Chinese Academy of Engineering. (Engineering 2016). 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. LighterCommunication 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). 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.

Patent Gilad-Bachrach Ran, Thomas W. Finley, Mikhail Bilenko, and Pengtao Xie. Neural networks for encrypted data. U.S. Patent Application 14/536,145, filed November 7, 2014.

Pengtao Xie

Research Experience Machine Learning Department, Carnegie Mellon University, August 2013 — present Graduate research assistant Advisor: Prof. Eric Xing

Microsoft Research, Redmond, WA, May 2014 — Aug 2014 Research intern in Cloud Machine Learning Team and Machine Learning Group Mentors: Dr. Thomas Finley, Dr. Misha Bilenko, Dr. Ran Gilad-Bachrach

Machine Learning Department, Carnegie Mellon University, Sept 2011 — Jul 2013 Visiting student in SAILING Lab. Advisor: Prof. Eric Xing

Robotics Institute, Carnegie Mellon University, May 2011 — Sept 2011 Visiting student in Human Sensing Lab Advisor: Prof. Fernando De la Torre

Microsoft Research Asia, China, Aug 2009 — Jun 2010 Research intern in Web Search and Mining group Mentor: Dr. Rong Xiao

Sichuan University, China, Feb 2009 — Jul 2009 Research Assistant in Machine Intelligence Lab, February 2009 — July 2009. Advisor: Prof. Jiancheng Lv

Teaching Experience Guest Lecturer in Carnegie Mellon University, Pittsburgh, PA 10708, Probabilistic Graphical Models. Instructor: Prof. Eric Xing, Spring 2017.

Teaching Assistant in Carnegie Mellon University, Pittsburgh, PA 10708, Probabilistic Graphical Models. Instructor: Prof. Eric Xing, Spring 2015. 10701, Machine Learning. Instructors: Prof. Barnabas Poczos and Prof. Aarti Singh, Spring 2014. 10601, Machine Learning. Instructors: Prof. William Cohen and Prof. Eric Xing, Fall 2013.

3

Pengtao Xie

4

Professional Activities Reviewer for British Machine Vision Conference (BMVC), 2017 Program Committee Member for European Conference on Machine Learning (ECML), 2017 Program Committee Member for International Conference on Artificial Intelligence and Statistics (AISTATS), 2017 Reviewer for PLOS ONE, 2017 Reviewer for Neural Information Processing Systems (NIPS), 2016 Program Committee Member for Asian Conference on Computer Vision (ACCV), 2016 Reviewer for European Conference on Computer Vision (ECCV), 2016 Program Committee Member for IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 20162017. Reviewer for Journal of the American Statistical Association (JASA). Program Committee Member for Annual Meeting of the Association for Computational Linguistics (ACL), 20152017. Reviewer for Conference on Empirical Methods in Natural Language Processing (EMNLP), 2015 Reviewer for International Conference on Computer Vision (ICCV), 2015, 2017 Reviewer for IEEE Transactions on Knowledge and Data Engineering (TKDE), 2015-2017 Reviewer for IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2015-2016 Reviewer for ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2015 Reviewer for International Conference on Machine Learning (ICML), 2014. Membership: ACM, IEEE.

Talks Database Seminar, Carnegie Mellon University, Mar 2016. Sufficient Factor Broadcasting for Distributed Machine Learning. 11th CSL Student Conference, University of Illinois Urbana-Champaign, Feb 2016. Latent Variable Modeling with Diversity-Inducing Mutual Angular Regularization. Artificial Intelligence Seminar, Carnegie Mellon University, Feb 2016. Diversity-Inducing Learning of Latent Variable Models: Frequentist and Bayesian Perspectives. VALSE Webinar, Oct 2015. Diversity Regularization of Latent Variable Models: Theory, Algorithm and Applications. Machine Learning Lunch Seminar, Carnegie Mellon University, Sept 2015. Mutual Angular Regularization of Latent Variable Models: Thoery, Algorithm and Applications. Beihang University, Aug 2015. Diversifying Restricted Boltzmann Machine for Document Modeling. ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Sydney, Aug 2015. Diversifying Restricted Boltzmann Machine for Document Modeling.

Pengtao Xie

5

VASC Seminar, Carnegie Mellon University, April 2015. Integrating Image Clustering and Codebook Learning. Machine Learning Lunch Seminar, Carnegie Mellon University, April 2015. Integrating Data Clustering and Representation Learning. SCS Student Seminar, Carnegie Mellon University, April 2015. Incorporating Word Correlation Knowledge into Topic Modeling. CL+NLP Seminar, Carnegie Mellon University, Apr 2015. Incorporating Word Correlation Knowledge into Topic Modeling. Database Seminar, Carnegie Mellon University, Mar 2015. Mining User Interests from Personal Photos. 29th AAAI Conference on Artificial Intelligence, Austin, Jan 2015. Integrating Image Clustering and Codebook Learning. Database Seminar, Carnegie Mellon University, Sep 2014. CryptGraph: Privacy Preserving Graph Analytics on Encrypted Graph. Machine Learning Lunch Seminar, Carnegie Mellon University, Sep 2014. Privacy Preserving Neural Network Prediction on Encrypted Data. Cylab Student Seminar, Carnegie Mellon University, Sep 2014. Privacy-Preserving Neural Network Prediction on Encrypted Data. SDI/ISTC Seminar, Carnegie Mellon University and Intel, Sep 2014. Privacy-Preserving Neural Network Prediction on Encrypted Data. Cloud Machine Learning Team and Machine Learning Group, Microsoft Research, Aug 2014. Privacy-Preserving Neural Network Prediction on Encrypted Data. Cryptography Group, Microsoft Research, Jul 2014. Privacy-Preserving Neural Network Prediction on Encrypted Data. 23rd International Joint Conference on Artificial Intelligence (IJCAI 2013), Beijing, Aug 2013. Multi-Modal Distance Metric Learning.

Awards and Honors KDD Travel Award, 2015. Siebel Scholarship, 2014 (85 graduate students from around the world). Excellent Master Graduate Award, Dept of CS, Tsinghua University, 2013. UAI 2013 Travel Scholarship, 2013. Excellent Bachelor Thesis Award, 2010. Excellent Bachelor Graduate Award, 2009. National Scholarship of China, 2009. First Class Sichuan University Scholarship, 2009. Sichuan University Excellent Student, 2009. Second Prize in Challenge Cup Technological Invention Competition, 2009.

Pengtao Xie

Third Prize in National English Contest for College Students, 2009. Successful Winner in Microsoft Imagine Cup Software Design Competition, 2009. Creative Talented Student Award granted by Sichuan University, 2009. Sichuan University Excellent Student Leader, 2008. National First Prize in China Undergraduate Mathematical Contest of Modeling, 2008. Gold Prize in Challenge Cup Entrepreneurship Contest of Sichuan Province, 2008. First Prize in Challenge Cup Entrepreneurship Contest of Sichuan University, 2008. Goldman Sachs Global Leader Scholarship, 2008 (150 undergraduate students from around the world). National Excitation Scholarship, 2007. Sichuan University Excellent Student Leader, 2007.

6