Kai Yu's Home Page

 

 

I am a researcher at NEC Laboratories America in California. Before joining NEC Labs, I was a senior research scientist at Siemens Corporate Technology at the lovely city Munich in Germany. I obtained my Ph.D in computer science from University of Munich (LMU), supervised by Prof. Hans-Peter Kriegel and Dr. Volker Tresp (Siemens AG), and received the B.Sc and M.Sc degrees both in electrical engineering from Nanjing University, China, in 1998 and 2000 respectively.

[Research Interests] [Research Links] [Publications] [Resume] [Contact Me] [Yan] [Friends]

Updates:

·        I have taught a graduate-level course “Data Mining” at University of California, Santa Cruz, for the Spring quarter 2009, April, 2009 

·        I’m co-organizing an ICML workshop on “learning feature hierarchies” with Ruslan Salakhutdinov, Yann LeCun, Geoffrey E. Hinton, and Yoshua Bengio, Febuary 2009 

·        2 papers in NIPS-08: one is about large-scale matrix factorization using MCMC and Gaussian processes, and the other is on learning deep neural networks using side information, September 2008 

·        1 paper get in ECCV-08 as an oral presentation, July, 2008 

·        1 paper get in SIGIR-08: active learning cast as a sparse learning problem, July 2008

·        See photos of my son, born on June 28 2007 

·        2 papers get in NIPS-07, September 4 2007 

·        2 papers accepted by ICML-07, and 1 paper accepted by SIGIR-07, May 21 2007 

·        NIPS06 paper and the data sets used in our experiments are now online available, Dec. 11 2006 

·        I joined in NEC Labs America in October 2006.

·        Photos from a vacation in the beautiful Greek island Santorini, May 2006

 

Research Interests

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·        Statistic machine learning, Bayesian probabilistic models, Gaussian Processes

·        Collaborative filtering, user modeling

·        Learning from relations

·        Multi-task learning

·        Text and web mining, data mining, and information retrieval

 

Professional Activities

 

Reviewers

·         Journals: Journal of Machine Learning Research, Machine Learning, IEEE Transactions on Neural Networks, IEEE Transactions on Knowledge and Data Engineering, ACM Transactions on Internet Technology, Pattern Recognition Letter

·         Conferences: NIPS (05, 06, 07, 08, 09), IJCAI (09), AISTATS (09), ICML (07, 08, 09), SIGIR (05, 06, 07, 08, 09), ECML (06), PKDD (06), PRICAI (08), ICMLA (08) 

 

Program Committee Members and Chairs

·        ICML Workshop on Learning Feature Hierarchies (09-co chair)

·        International Asian Conference on Machine Learning (ACML 09)

·        International Joint Conference on Artificial Intelligence (IJCAI 09)

·        International Conference on AI and Statistics (AISTAT 09)

·        International Conference on Machine Learning (ICML 07, 08, 09-session chair)

·        International ACM SIGIR Conference, (SIGIR 06, 07, 08, 09)

·        International ACM SIGKDD Conference (KDD 08, 09)

·        KDD 2008 Workshop on Data Mining Using Matrices and Tensors (DMMT 08)

·        NIPS08 Workshop on Cost Sensitive Learning

·        International SIGIR Workshop on Learning to Rank for Information Retrieval (07, 08)

·        International ACM Conference on Information and Knowledge Management (CIKM 08 09)

·        Pacific Rim International Conference on Artificial Intelligence (PRICAI 08)

·        European Conference on Machine Learning (ECML 06)

·        European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD 06)

·        International Workshop on Nonparametric Bayesian Methods at ICML 06

 

Selected Publications [complete list]

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2009

·       High-dimensional Nonlinear Learning using Local Coordinate Coding [pdf]

Kai Yu and Tong Zhang

Technical Report

 

·       Large-scale Collaborative Prediction Using a Nonparametric Random Effects Model [pdf] [slides]

Kai Yu, John Lafferty, Shenghuo Zhu, and Yihong Gong

Proceedings of the 26th International Conference on Machine Learning (ICML 2009)

A note on inverted Wishart distributions.

 

·       Fast Nonparametric Matrix Factorization for Large-scale Collaborative Filtering [pdf] [code]

Kai Yu, Shenghuo Zhu, John Lafferty, and Yihong Gong

To appear in Proceedings of the 32nd Annual International ACM SIGIR Conference (SIGIR 2009)

 

·       Linear Spatial Pyramid Matching Using Sparse Coding for Image Classification [more info]

Jianchao Yang, Kai Yu, Yihong Gong, and Thomas Huang

To appear in IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2009)

 

·       Deep Learning with Kernel Regularization for Visual Recognition [pdf]

Kai Yu, Wei Xu, and Yihong Gong

Advances in Neural Information Processing Systems 21 (NIPS 2008)

(Eds.) D. Koller, Y. Bengio, D. Schuurmans and L. Bottou, MIT Press, Cambridge, MA, USA, 2009

 

·       Stochastic Relational Models for Large-scale Dyadic Data using MCMC [pdf] [code]

Shenghuo Zhu, Kai Yu and Yihong Gong

Advances in Neural Information Processing Systems 21 (NIPS 2008)

(Eds.) D. Koller, Y. Bengio, D. Schuurmans and L. Bottou, MIT Press, Cambridge, MA, USA, 2009

 

 

2008

·       Training Hierarchical Feed-forward Visual Recognition Models Using Transfer Learning from Pseudo Tasks [pdf]

Amr Ahmed, Kai Yu, Wei Xu, Yihong Gong and Eric P. Xing

The 10th European Conference on Computer Vision, (ECCV 08)

Oral presentation, acceptance rate 4.6% 

 

·       Feature Selection for Gene Expression using Model-based Entropy [draft]

Shenghuo Zhu, Dingding Wang, Kai Yu, Tao Li, and Yihong Gong.

IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2008

 

·       Nonparametric Relational Learning for Social Network Analysis [pdf]

Zhao Xu, Volker Tresp, Shipeng Yu, and Kai Yu.

The 2nd KDD workshop on Social Network Mining and Analysis, (SNA-KDD 08)

 

·       Non-greedy Active Learning for Text Categorization using Convex Transductive Experimental Design [pdf]

Kai Yu, Shenghuo Zhu, Wei Xu, and Yihong Gong

Proceedings of the 31st Annual International ACM SIGIR Conference (SIGIR 08)

 

·       Learning Multiple Graphs for Document Recommendations [pdf]

Ding Zhou, Shenghuo Zhu, Kai Yu, Xiaodan Song, Belle Tseng, Hongyuan Zha, and C.Lee Giles

Proceedings of the 17th International World Wide Web Conference (WWW08)

 

·       Gaussian Process Models for Link Analysis and Transfer Learning [pdf]

Kai Yu and Wei Chu

Advances in Neural Information Processing Systems 20 (NIPS 2007)

(Eds.) Platt, J. C., D. Koller, Y. Singer, S. Roweis, MIT Press, Cambridge, MA, USA, 2008

 

·       Predictive Matrix-Variate t Models [pdf]

Shenghuo Zhu, Kai Yu and Yihong Gong

Advances in Neural Information Processing Systems 20 (NIPS 2007)

(Eds.) Platt, J. C., D. Koller, Y. Singer, S. Roweis, MIT Press, Cambridge, MA, USA, 2008

 

 

2007

·       Robust Multi-Task Learning with t-Processes [pdf]

Shipeng Yu, Volker Tresp, Kai Yu, and Bharat Rao

Proceedings of the 24th International Conference on Machine Learning (ICML 2007)

 

·       Local Learning Projection [pdf]

Mingrui Wu, Kai Yu, Shipeng Yu, and Bernhard Schölkopf

Proceedings of the 24th International Conference on Machine Learning (ICML 2007)

 

·       Combining Contents and Links for Classification using Matrix Factorization [pdf]

Shenghuo Zhu, Kai Yu, Yun Chi, and Yihong Gong

Proceedings of the 30th Annual International ACM SIGIR Conference (SIGIR 2007)

 

·       Stochastic Relational Models for Discriminative Link Prediction [pdf] [data]

Kai Yu, Wei Chu, Shipeng Yu, Volker Tresp, and Zhao Xu

Advances in Neural Information Processing Systems 19 (NIPS 2006),

(Eds.) B. Schölkopf, J. C. Platt and T. Hofmann, MIT Press, Cambridge, MA USA, 2007

 

 

2006

·       Multi-Output Regularized Feature Projection [Link]

Shipeng Yu, Kai Yu, Volker Tresp, and Hans-Peter Kriegel.
IEEE Transactions on Knowledge and Data Engineering (TKDE),

18 (22), pp. 1600-1613,  December 2006.

 

·       Variational  Bayesian Dirichlet-Multinomial Allocation for Exponential Family Mixtures 

Shipeng Yu, Kai Yu, and Volker Tresp, 

Proceedings of the 17th European Conference on Machine Learning  (ECML 2006), 2006 

 

·       Supervised Probabilistic Principal Component Analysis [pdf] 

Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Kriegel, and Mingrui Wu

Proceedings of the 12th International Conference on Knowledge Discovery and Data Mining (SIGKDD 2006), 2006 

(Acceptance Rate <11%)

 

·       Infinite Hidden Relational Models [pdf]

Zhao Xu, Volker Tresp, Kai Yu, and Hans-Peter Kriegel, 

Proceedings of the 22nd International Conference on Uncertainty in Artificial Intelligence (UAI 2006), 2006 

 

·       Active Learning via Transductive Experimental Design [pdf] [matlab code & data] 

Kai Yu, Jinbo Bi, and Volker Tresp, 

Proceedings of the 23rd  International Conference on Machine Learning (ICML 2006), 2006 

 

·       Collaborative Ordinal Regression [pdf]

Shipeng Yu, Kai Yu, and Volker Tresp, 

Proceedings of the 23rd  International Conference on Machine Learning (ICML 2006), 2006

 

·       Soft Clustering on Graphs [pdf]

Kai Yu, Shipeng Yu, and Volker Tresp, 

Advances in Neural Information Processing Systems 18 (NIPS 2005),

(Eds.) Y. Weiss, B. Schölkopf, and J. Platt, MIT Press, Cambridge, MA USA, 2006

 

 

2005

·       Learning to Learn and Collaborative Filtering [pdf]

Kai Yu and Volker Tresp, 

Workshop on Inductive Transfer: 10 Years Later (NIPS*05 Workshop),

Whistler, Canada, Dec. 2005

 

·       A Probabilistic Clustering-Projection Model for Discrete Data  [pdf]

Shipeng Yu, Kai Yu, Volker Tresp, and Hans-Peter Kriegel, 

Proceedings of the 9th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD 2005),

Porto, Portugal, October 3-7, 2005. (Best Paper Runner-up Award)

 

·       Learning Gaussian Processes from Multiple Tasks [pdf] [slides]

Kai Yu, Volker Tresp, and Anton Schwaighofer,  

Proceedings of the 22nd International Conference on Machine Learning (ICML 2005),

Bonn, Germany, 7-11 August, 2005

 

·       Dirichlet Enhanced Probabilistic Relational Model  [pdf]

Zhao Xu, Volker Tresp, Kai Yu, Shipeng Yu, and Hans-Peter Kriegel,  

Proceedings of the 22nd International Conference on Machine Learning (ICML 2005),

Bonn, Germany, 7-11 August, 2005

 

·       Blockwise Supervised Inference on Large Graphs [pdf]

     Kai Yu, Shipeng Yu, and Volker Tresp,  

Workshop on Learning with Partially Classified Training Data (ICML 2005 Workshop),

at the 22nd International Conference on Machine Learning, Bonn, Germany, 7-11 August, 2005

 

·       Multi-Output Regularized Projection  [pdf]

Kai Yu, Shipeng Yu, and Volker Tresp, 

Proceedings of International IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2005),

San Diego, CA, USA,  June 20-26, 2005.

 

·       Learning Gaussian Process Kernels via Hierarchical Bayes  [pdf]

     Anton Schwaighofer, Volker Tresp, and Kai Yu,  

Advances in Neural Information Processing Systems 17 (NIPS 2004).

(Eds.) Saul, L.K., Y. Weiss and L. Bottou, MIT Press, Cambridge, MA, USA, 2005.

 

·       Dirichlet Enhanced Latent Semantic Analysis  [pdf]

Kai Yu, Shipeng Yu, and Volker Tresp, 

Proceedings of Artificial Intelligence & Statistics (AISTATS 2005),

Barbados, January 6-8, 2005.

 

·      Multi-Label Informed Latent Semantic Indexing  [pdf]

Kai Yu, Shipeng Yu, and Volker Tresp, 

Proceedings of the 28th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2005),

August 15-19, 2005, in Salvador, Brazil.

 

2004

·       A Nonparametric Hierarchical Bayesian Framework for Information Filtering  [pdf]

Kai Yu, Volker Tresp, and Shipeng Yu, 

Proceedings of the 27th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2004),

Sheffield, UK, July 25 - 29, 2004.

 

·       An introduction to nonparametric hierarchical Bayesian modelling with a focus on multi-agent learning [pdf]

            Volker Tresp and Kai Yu.

      book chapter, Switching and Learning in Feedback Systems. Springer, 2004.

 

·       Probabilistic Memory-Based Collaborative Filtering [draft]

            Kai Yu, Anton Schwaighofer, Volker Tresp, Xiaowei Xu, Hans-Peter Kriegel

     IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol.16, No.1, pp. 56--69, 2004.

 

2003

·       Approximate Solutions to Nonparametric Bayesian Hierarchical Modelling with Applications to Information Filtering [link]

            Volker Tresp, Kai Yu, Anton Schwaighofer,

     Nonparametric Bayesian Methods and Infinite Models, (NIPS*03 Workshop),

     Vancouver, Dec. 2003.

 

·       Collaborative Ensemble Learning: Combining Collaborative and Content-Based Information Filtering via Hierarchical Bayes [pdf]

            Kai Yu, Anton Schwaighofer, Volker Tresp, Wei-Ying Ma, Hongjiang Zhang,

     Proceedings of the 19th International Conference on Uncertainty in Artificial Intelligence (UAI 2003),

     Acapulco, Mexico, August 7-10, 2003. (Plenary oral presentation, 11% accepted)

 

·       Knowing a Tree from the Forest: Art Image Retrieval using a Society of Profiles [pdf]

            Kai Yu, Wei-Ying Ma, Volker Tresp, Zhao Xu, Xiaofei He, Hongjiang Zhang and Hans-Peter Kriegel,

     Proceedings of the 11th Annual ACM International Conference on Multimedia (ACM Multimedia 2003),

     Berkeley, CA, USA, November 2-8, 2003.

Contact Me

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Email:      kyu (at) sv dot nec-labs dot com,   kai.yu.cool (at) googlemail

Tel:          +1 408 863 6022

Fax:         +1 408 863 6099

  • Last updated July 02, 2009.