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Machine learning : a probabilistic perspective

. Adaptive computation and machine learning series MIT, Cambridge, MA, (2012)

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Modeling changing dependency structure in multivariate time series., и . ICML, том 227 из ACM International Conference Proceeding Series, стр. 1055-1062. ACM, (2007)Object Detection and Localization Using Local and Global Features., , , и . Toward Category-Level Object Recognition, том 4170 из Lecture Notes in Computer Science, стр. 382-400. Springer, (2006)Markov and Hidden Markov Models. Machine Learning: A Probabilistic Approach, MIT Press, Cambridge, MA, USA, (2012)Bayesian statistics. Machine Learning: A Probabilistic Approach, MIT Press, Cambridge, MA, USA, (2012)Generative models for discrete data. Machine Learning: A Probabilistic Approach, MIT Press, Cambridge, MA, USA, (2012)Machine learning : a probabilistic perspective. MIT Press, Cambridge, Mass. u.a., (2013)Multiscale Conditional Random Fields for Semi-supervised Labeling and Classification., , и . CRV, стр. 371-378. IEEE Computer Society, (2011)A Dynamic Bayesian Network Approach to Figure Tracking using Learned Dynamic Models., , , и . ICCV, стр. 94-101. IEEE Computer Society, (1999)Vision-Based Speaker Detection Using Bayesian Networks., , и . CVPR, стр. 2110-2116. IEEE Computer Society, (1999)A coupled HMM for audio-visual speech recognition., , , , , и . ICASSP, стр. 2013-2016. IEEE, (2002)