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Probabilistic Graphical Models for Human Interaction Analysis

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Modeling Individual and Group Actions in Meetings With Layered HMMs

Daniel Gatica-Perez, Samy Bengio, Guillaume Lathoud, Dong Zhang

We address the problem of recognizing sequences of human interaction patterns in meetings, with the goal of structuring them in semantic terms. The investigated patterns are inherently group-based (defined by the individual activities of meeting participan ...

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Modeling Individual and Group Actions in Meetings With Layered HMMs

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I present an introduction to some of the concepts within Bayesian networks to help a beginner become familiar with this field's theory. Bayesian networks are a combination of two different mathematical areas: graph theory and probability theory. So, I firs ...

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In a society which produces and consumes an ever increasing amount of information, methods which can make sense out of al1 this data become of crucial importance. Machine learning tries to develop models which can make the information load accessible. Thre ...

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We emphasize the need for input-dependent regularization in the context of conditional density models (also: discriminative models) like Gaussian process predictors. This can be achieved by a simple modification of the standard Bayesian data generation mod ...

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Randomization in the two-parameter optimal stopping problem

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The motivation to this research is the study of the optimal stopping problem for multiparameter processes : given a random process depending on finitely many parameters t = (t1,…,tn), which if stopped at point t in the parameter set produces a reward Xt, w ...

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The success of the P2P idea has created a huge diversity of approaches, among which overlay networks, for example, Gnutella, Kazaa, Chord, Pastry, Tapestry, P-Grid, or DKS, have received specificc attention from both developers and researchers. A wide vari ...