Bayesian Conditional Random Fields, Yuan Qi, Martin Szummer, and Thomas P. Minka, To appear in AISTATS 2005. [paper/pdf]

Predictive Automatic Relevance Determination by Expectation Propagation, Yuan Qi, Thomas P. Minka, Rosalind W. Picard, and Zoubin Ghahramani, in the Proceedings of Twenty-first International Conference on Machine Learning, July 4-8, 2004, Banff, Alberta, Canada. [paper/pdf] and [slides/ppt]
Bayesian sparse classifiers, which were applied to gene expression classification.

Tree-structured Approximations by Expectation Propagation, Thomas Minka and Yuan Qi, Neural Information Processing Systems, December 2003, British Columbia, Canada. [pdf]

 
Expectation Propagation for Signal Detection in Flat-fading Channels, Yuan Qi and Thomas Minka, MIT Media Lab  Technical Report Vismod-TR-555. Also, in the Proceedings of IEEE International Symposium on Information Theory, June, 2003, Yokohama, Japan. [Abstract] and  [Paper /pdf /ps].

An efficient fixed-lag smoothing algorithm for hybrid dynamic Bayesian networks with its application to wireless communications.

Questions and answers about philosophy of science, causation, and human/machine learning, Yuan Qi, October 2002, [pdf/ps]. 

Context-sensitive Bayesian Classifiers and  Application to Mouse Pressure Pattern Classification, Yuan Qi,  and Rosalind W. Picard, in Proceedings of International Conference on Pattern Recognition, August 2002, Québec City, Canada. [slide/ps] and [Paper/pdf].
A simple probabilistic way to combine multiple classifiers which are trained on different subsets of  a given training set.

Bayesian Spectrum Estimation of Unevenly Sampled Nonstationary Data, Yuan Qi, Thomas P. Minka, and Rosalind W. Picard, MIT Media Lab  Technical Report Vismod-TR-556,  [Abstract]  and  [Paper/pdf].

Check out this web page that summarizes experimental results, including comparison with  classical methods, e.g., Multitaper methods. The short version of this paper does not include sparsification techniques and appears in ICASSP 02, May 2002, Orlando, Florida. [Poster/pdf] and [Paper/pdf].

Hybrid Independent Component Analysis and Support Vector Machine Learning Scheme for Face Detection, Y. Qi, D. DeMenthon, and D. Doermann, International Conference on Acoustics, Speech, and Signal Processing (ICASSP01), May 2001, Salt Lake City,Utah. [ps]

Learning Algorithms for Video and Audio Processing: Independent Component Analysis and Support Vector Machine based Approaches,  Yuan Qi, Technical Report LAMP-TR-056, CAR-TR-951, CS-TR-4174, Center for Automation Research, University of Maryland at College Park, August 2000.

Subband-based Independent Component Analysis, Yuan Qi, S.A. Shamma, P.S. Krishnaprasad, Proceedings of ICA2000,19-22 June 2000, Helsinki, Finland.

Talks

Extending expectation propagation for graphical models, CMU CALD Machine learning lunch, April, 2004

Software