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I am Kai Yu, a PhD student at the Database
Group of Computer Science Department at the University of Munich (LMU),
supervised by Prof.
Hans-Peter Kriegel. My study and research are funded through a joint Ph.D
program between LMU and
Siemens AG. Currently I am doing my research with Anton
Schwaighofer, directed by Dr.
Volker Tresp, at Siemens
Corporate Technology. My research is mainly focused on statistical machine
learning and its applications to information filtering, image retrieval and
medical data analysis. I received the
B.Sc and M.Sc degrees both in electrical engineering from Nanjing
University, China, in 1998 and 2000 respectively. Dear visitors, please take a few minutes to attend an online survey about your preferences for painting images. Thanks! |
· Statistic machine learning and data mining
· Hidden variable analysis using Baysian inference
· Intelligent
text and image retrieval (including hybrid supervised / unsupervised learning,
active learning)
· Collaborative
filtering with applications in recommender systems
· Speech separation and noise reduction with Wiener filtering
In this research, we wish to demonstrate that
artificial intelligence technology can do a fancy job to help people enjoy the
beauty of art paintings!
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· K. Yu, V. Tresp and A. Schwaighofer, A Generalized Principal Component Analysis for Mixed Data, 2003
· V. Tresp, K. Yu and A. Schwaighofer, An Infinite-Dimensional Multinomial Model with Applications to Hierarchical Bayes, 2003
PhD Thesis:
Kai Yu, Statistical Learning Approaches to Information Filtering, submitted dissertation for Doctoral degree in Computer Science, University of Munich, Dec.2003.
Defense Committee:
Reviewers: Prof. Dr. Hans-Peter Kriegel (LMU), Prof. Dr. Jiawei Han (UIUC), Dr. Volker Tresp (Siemens)
Examinators: Prof. Dr. Martin Wirsing (LMU), Prof. Dr. Ralf Zimmer (LMU)
· K.
Yu, A. Schwaighofer, V. Tresp, X. Xu, H.-P. Kriegel: Probabilistic
Memory-Based Collaborative Filtering, IEEE Transactions on Knowledge and Data Engineering
(TKDE), Vol.16, No.1, pp. 56--69, special
issue on Mining and Searching the Web, 2003.
· K. Yu, X. Xu, M. Ester, H.-P. Kriegel: Feature Weighting and Instance Selection for Collaborative Filtering: An Information-Theoretic Approach, Knowledge and Information Systems (KAIS), Springer-Verlag, Vol. 5, No. 2, April, 2003. [abstract]
· K. Yu, V. Tresp, and S. Yu, A Nonparametric Hierarchical Bayesian Framework for Information Filtering,
to appear in Proceedings of 27th Annual International ACM Conference on
Research and Development in Information Retrieval (SIGIR 2004),
Sheffield,
UK, July 25 - 29, 2004.
· K. Yu, and V. Tresp, Heterogenous Data Fusion via a Probabilistic Latent-Variable Model, in Proceedings of
17th International Conference on Architecture of Computing Systems - Organic and Pervasive Computing (ARCS 2004),
Lecture Notes in Computer Science (LNCS 2981), Springer Verlag, Augsburg, Germany, March, 2004.
· K. Yu, W.-Y. Ma, V. Tresp, Z. Xu, X. He, H.J. Zhang and H.-P. Kriegel, Knowing a Tree from the Forest: Art Image Retrieval using a Society of Profiles, Proceedings of 11th Annual ACM International Conference on Multimedia (ACM Multimedia'03), Berkeley, CA, USA, November 2-8, 2003. [pdf]
· K. Yu, A. Schwaighofer, V. Tresp, W.-Y. Ma, H.J. Zhang, Collaborative Ensemble Learning: Combining Collaborative and Content-Based Information Filtering via Hierarchical Bayes, Proceedings of 19th International Conference on Uncertainty in Artificial Intelligence (UAI'03), Acapulco, Mexico, August 7-10, 2003. [pdf]
· Z.
Xu, K. Yu V. Tresp, X. Xu, and J. Wang: Representative Sampling for
Text Classification using Support Vector Machines, the 25th
European Conference on Information Retrieval Research (ECIR'03), Lecture
Notes in Computer Science (LNCS 2633), Springer, Pisa, Italy
- April 14-16, 2003
· Z. Xu, X. Xu, K. Yu, V. Tresp, and J. Wang: A Hybrid Relevance-Feedback Approach to Text Retrieval, the 25th European Conference on Information Retrieval Research (ECIR'03), Lecture Notes in Computer Science (LNCS 2633), Springer, Pisa, Italy - April 14-16, 2003 [pdf]
· K. Yu, X. Xu, A. Schwaighofer, V. Tresp, and H.-P. Kriegel: Removing Redundancy and Inconsistency in Memory-Based Collaborative Filtering, Proc. ACM 11th Int. Conf. on Information and Knowledge Management (CIKM'02), McLean, VA, Nov. 2002. [pdf]
· K.
Yu,
X. Xu, J. Tao,
M. Ester, and H.-P. Kriegel: Instance Selection Techniques
for Memory-Based Collaborative Filtering, Proc. 2nd SIAM Int. Conf. on
Data Mining (SDM'02), Arlington, VA, 2002.
· K.
Yu, X. Xu, M. Ester, and H.-P. Kriegel: Selecting Relevant Instances for
Efficient and Accurate Collaborative Filtering, Proc. ACM 10th Int.
Conf. on Information and Knowledge Management (CIKM'01), pp. 247-254, 2001.
· K.
Yu, Z. Wen, X. Xu, and M. Ester: Feature Weighting and Instance Selection for
Collaborative Filtering, Proc. 2nd Int. Workshop on Management of
Information on the Web - Web Data and Text Mining (MIW'01), pp. 285-290, 2001.
· Y.
Gao,
J. Lu, K. Yu,
and B.
Xu: Iterative Noise Cancellation with
Applications to Speech Enhancement, in Proceedings of the 26th IEEE
Conf. on Acoustics, Speech and Signal Processing (ICASSP'01), vol. 1, 2001, Salt
Lake City, USA, 2001
· K.
Yu, B. Xu, M. Dai, and C. Yu: Suppressing Cocktail Party Noise for
Speech Acquisition, The 5th International Conference on
Signal Processing (ICSP'00), Beijing China, Aug. 21-25, 2000.
· M. Dai, K. Yu, B. Xu, and C. Yu: Low SNR Robust Chinese Tone Extraction Based on Human Auditory Model, The 5th International Conference on Signal Processing (ICSP'00), Beijing China, Aug. 21-25, 2000.
· K. Yu, B. Xu, M. Dai, C. Yu: Iterative Speech Separation Controlled by Difference Phase - Correlation - Based Criterion Function, Journal of the Acoustics Society of China, Vol.04, 2001 (in Chinese).
Email:
kai.yu(at)gmx.net,
yu_k(at)dbs.informatik.uni-muenchen.de , kai.yu.external(at)mchp.siemens.de
Tel:
+49 89 636 47926
Fax: +49 89 636 45456
Home Page: http://www.dbs.informatik.uni-muenchen.de/~yu_k/ http://www.geocities.com/kai_fisher/