Thomas P. Minka

Thomas P. Minka, John D. Lafferty: Expectation-Propogation for the Generative Aspect Model. CoRR abs/1301.0588 (2013)

Thomas P. Minka: Expectation Propagation for approximate Bayesian inference. CoRR abs/1301.2294 (2013)

Yoram Bachrach, Thore Graepel, Tom Minka, John Guiver: How To Grade a Test Without Knowing the Answers - A Bayesian Graphical Model for Adaptive Crowdsourcing and Aptitude Testing. ICML 2012

Souvik Sen, Bozidar Radunovic, Romit Roy Choudhury, Tom Minka: You are facing the Mona Lisa: spot localization using PHY layer information. MobiSys 2012: 183-196

Yuan Qi, Ahmed H. Abdel-Gawad, Thomas P. Minka: Sparse-posterior Gaussian Processes for general likelihoods. CoRR abs/1203.3507 (2012)

Thomas P. Minka, Rongjing Xiang, Yuan (Alan) Qi: Virtual Vector Machine for Bayesian Online Classification. CoRR abs/1205.2623 (2012)

Max Welling, Thomas P. Minka, Yee Whye Teh: Structured Region Graphs: Morphing EP into GBP. CoRR abs/1207.1426 (2012)

Souvik Sen, Romit Roy Choudhury, Bozidar Radunovic, Tom Minka: Precise indoor localization using PHY layer information. HotNets 2011: 18

Souvik Sen, Bozidar Radunovic, Romit Roy Choudhury, Tom Minka: Precise indoor localization using PHY information. MobiSys 2011: 413-414

David A. Knowles, Tom Minka: Non-conjugate Variational Message Passing for Multinomial and Binary Regression. NIPS 2011: 1701-1709

Yuan (Alan) Qi, Ahmed H. Abdel-Gawad, Thomas P. Minka: Sparse-posterior Gaussian Processes for general likelihoods. UAI 2010: 450-457

Zeyuan Allen Zhu, Weizhu Chen, Tom Minka, Chenguang Zhu, Zheng Chen: A novel click model and its applications to online advertising. WSDM 2010: 321-330

Thomas P. Minka, Rongjing Xiang, Yuan (Alan) Qi: Virtual Vector Machine for Bayesian Online Classification. UAI 2009: 411-418

Fan Guo, Chao Liu, Anitha Kannan, Tom Minka, Michael J. Taylor, Yi Min Wang, Christos Faloutsos: Click chain model in web search. WWW 2009: 11-20

Yuan Qi, Ahmed H. Abdel-Gawad, Thomas P. Minka: Variable sigma Gaussian processes: An expectation propagation perspective. CoRR abs/0910.0668 (2009)

Peter V. Gehler, Carsten Rother, Andrew Blake, Thomas P. Minka, Toby Sharp: Bayesian color constancy revisited. CVPR 2008

Tom Minka, John M. Winn: Gates. NIPS 2008: 1073-1080

Michael J. Taylor, John Guiver, Stephen Robertson, Tom Minka: SoftRank: optimizing non-smooth rank metrics. WSDM 2008: 77-86

Yuan Qi, Thomas P. Minka: Window-based expectation propagation for adaptive signal detection in flat-fading channels. IEEE Transactions on Wireless Communications 6(1): 348-355 (2007)

Pierre Dangauthier, Ralf Herbrich, Tom Minka, Thore Graepel: TrueSkill Through Time: Revisiting the History of Chess. NIPS 2007

Julia A. Lasserre, Christopher M. Bishop, Thomas P. Minka: Principled Hybrids of Generative and Discriminative Models. CVPR (1) 2006: 87-94

Carsten Rother, Thomas P. Minka, Andrew Blake, Vladimir Kolmogorov: Cosegmentation of Image Pairs by Histogram Matching - Incorporating a Global Constraint into MRFs. CVPR (1) 2006: 993-1000

Ralf Herbrich, Tom Minka, Thore Graepel: TrueSkill^TM: A Bayesian Skill Rating System. NIPS 2006: 569-576

Yuan (Alan) Qi, Martin Szummer, Thomas P. Minka: Diagram Structure Recognition by Bayesian Conditional Random Fields. CVPR (2) 2005: 191-196

John M. Winn, Antonio Criminisi, Thomas P. Minka: Object Categorization by Learned Universal Visual Dictionary. ICCV 2005: 1800-1807

Max Welling, Thomas P. Minka, Yee Whye Teh: Structured Region Graphs: Morphing EP into GBP. UAI 2005: 609-614

Yuan (Alan) Qi, Thomas P. Minka, Rosalind W. Picard, Zoubin Ghahramani: Predictive automatic relevance determination by expectation propagation. ICML 2004

Thomas P. Minka, Yuan (Alan) Qi: Tree-structured Approximations by Expectation Propagation. NIPS 2003

Charles R. Rosenberg, Thomas P. Minka, Alok Ladsariya: Bayesian Color Constancy with Non-Gaussian Models. NIPS 2003

Yuan Qi, Thomas P. Minka, Rosalind W. Picard: Bayesian spectrum estimation of unevenly sampled nonstationary data. ICASSP 2002: 1473-1476

Yi Zhang, James P. Callan, Thomas P. Minka: Novelty and redundancy detection in adaptive filtering. SIGIR 2002: 81-88

Thomas P. Minka, John D. Lafferty: Expectation-Propogation for the Generative Aspect Model. UAI 2002: 352-359

Thomas V. Papathomas, Ingemar J. Cox, Peter N. Yianilos, Matthew L. Miller, Thomas P. Minka, Tiffany E. Conway, Joumana Ghosn: Psychophysical experiments on the PicHunter image retrieval system. J. Electronic Imaging 10(1): 170-180 (2001)

Dan S. Bloomberg, Kris Popat, Thomas P. Minka: Document Image Decoding Using Iterated Complete Path Search with Subsampled Heuristic Scoring. ICDAR 2001: 344-349

Thomas P. Minka: Expectation Propagation for approximate Bayesian inference. UAI 2001: 362-369

Ingemar J. Cox, Matthew L. Miller, Thomas P. Minka, Thomas V. Papathomas, Peter N. Yianilos: The Bayesian image retrieval system, PicHunter: theory, implementation, and psychophysical experiments. IEEE Transactions on Image Processing 9(1): 20-37 (2000)

Ingemar J. Cox, Matthew L. Miller, Thomas P. Minka, Thomas V. Papathomas, Peter N. Yianilos: Correction to "the Bayesian image retrieval system, pichunter: theory, implementation, and psychophysical experiments". IEEE Transactions on Image Processing 9(3): 524- (2000)

Thomas P. Minka: Automatic Choice of Dimensionality for PCA. NIPS 2000: 598-604

Ingemar J. Cox, Matthew L. Miller, Thomas P. Minka, Peter N. Yianilos: An Optimized Interaction Strategy for Bayesian Relevance Feedback. CVPR 1998: 553-558

Thomas P. Minka, Rosalind W. Picard: Interactive learning with a "society of models". Pattern Recognition 30(4): 565-581 (1997)

Thomas P. Minka, Rosalind W. Picard: Interactive Learning with a "Society of Models" . CVPR 1996: 447-452

Rosalind W. Picard, Thomas P. Minka, Martin Szummer: Modeling user subjectivity in image libraries. ICIP (2) 1996: 777-780

Rosalind W. Picard, Thomas P. Minka: Vision Texture for Annotation. Multimedia Syst. 3(1): 3-14 (1995)