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JMLR
2012
11 years 6 months ago
Bayesian regularization of non-homogeneous dynamic Bayesian networks by globally coupling interaction parameters
To relax the homogeneity assumption of classical dynamic Bayesian networks (DBNs), various recent studies have combined DBNs with multiple changepoint processes. The underlying as...
Marco Grzegorczyk, Dirk Husmeier
PR
2011
12 years 7 months ago
Detecting and discriminating behavioural anomalies
This paper aims to address the problem of anomaly detection and discrimination in complex behaviours, where anomalies are subtle and difficult to detect owing to the complex tempo...
Chen Change Loy, Tao Xiang, Shaogang Gong
ICASSP
2011
IEEE
12 years 8 months ago
Lexical access experiments with context-dependent articulatory feature-based models
We address the problem of pronunciation variation in conversational speech with a context-dependent articulatory featurebased model. The model is an extension of previous work usi...
Preethi Jyothi, Karen Livescu, Eric Fosler-Lussier
JMLR
2010
140views more  JMLR 2010»
12 years 11 months ago
Learning Non-Stationary Dynamic Bayesian Networks
Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
Joshua W. Robinson, Alexander J. Hartemink
EXPERT
2010
145views more  EXPERT 2010»
13 years 1 months ago
Interaction Analysis with a Bayesian Trajectory Model
Human behavior recognition is one of the most important and challenging objectives performed by intelligent vision systems. Several issues must be faced in this domain ranging fro...
Alessio Dore, Carlo S. Regazzoni
KI
2010
Springer
13 years 2 months ago
Situation-Specific Intention Recognition for Human-Robot Cooperation
Recognizing human intentions is part of the decision process in many technical devices. In order to achieve natural interaction, the required estimation quality and the used comput...
Peter Krauthausen, Uwe D. Hanebeck
ACL
2010
13 years 2 months ago
Phrase-Based Statistical Language Generation Using Graphical Models and Active Learning
Most previous work on trainable language generation has focused on two paradigms: (a) using a statistical model to rank a set of generated utterances, or (b) using statistics to i...
François Mairesse, Milica Gasic, Filip Jurc...
ICML
2010
IEEE
13 years 2 months ago
Heterogeneous Continuous Dynamic Bayesian Networks with Flexible Structure and Inter-Time Segment Information Sharing
Classical dynamic Bayesian networks (DBNs) are based on the homogeneous Markov assumption and cannot deal with heterogeneity and non-stationarity in temporal processes. Various ap...
Frank Dondelinger, Sophie Lebre, Dirk Husmeier
IJAR
2002
102views more  IJAR 2002»
13 years 4 months ago
Networks of probabilistic events in discrete time
The usual methods of applying Bayesian networks to the modeling of temporal processes, such as Dean and Kanazawa's dynamic Bayesian networks (DBNs), consist in discretizing t...
Severino F. Galán, Francisco Javier D&iacut...
JMM2
2007
122views more  JMM2 2007»
13 years 4 months ago
Hierarchical Model-Based Activity Recognition With Automatic Low-Level State Discovery
Abstract— Activity recognition in video streams is increasingly important for both the computer vision and artificial intelligence communities. Activity recognition has many app...
Justin Muncaster, Yunqian Ma