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» Dynamic Modeling in Inductive Inference
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ICASSP
2009
IEEE
13 years 5 months ago
Spoken language interpretation: On the use of dynamic Bayesian networks for semantic composition
In the context of spoken language interpretation, this paper introduces a stochastic approach to infer and compose semantic structures. Semantic frame structures are directly deri...
Marie-Jean Meurs, Fabrice Lefevre, Renato de Mori
FGR
2011
IEEE
176views Biometrics» more  FGR 2011»
12 years 11 months ago
Prop-free pointing detection in dynamic cluttered environments
Abstract—Vision-based prop-free pointing detection is challenging both from an algorithmic and a systems standpoint. From a computer vision perspective, accurately determining wh...
Pyry Matikainen, Padmanabhan Pillai, Lily B. Mumme...
PR
2006
112views more  PR 2006»
13 years 8 months ago
Understanding gestures with systematic variations in movement dynamics
Sign language communication includes not only lexical sign gestures but also grammatical processes which represent inflections through systematic variations in sign appearance. We...
Sylvie C. W. Ong, Surendra Ranganath, Yedatore Ven...
AAAI
2012
11 years 10 months ago
Advances in Lifted Importance Sampling
We consider lifted importance sampling (LIS), a previously proposed approximate inference algorithm for statistical relational learning (SRL) models. LIS achieves substantial vari...
Vibhav Gogate, Abhay Kumar Jha, Deepak Venugopal
ICMLA
2008
13 years 9 months ago
A Bayesian Approach to Switching Linear Gaussian State-Space Models for Unsupervised Time-Series Segmentation
Time-series segmentation in the fully unsupervised scenario in which the number of segment-types is a priori unknown is a fundamental problem in many applications. We propose a Ba...
Silvia Chiappa