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AAAI
2004
15 years 1 months ago
Bayesian Inference on Principal Component Analysis Using Reversible Jump Markov Chain Monte Carlo
Based on the probabilistic reformulation of principal component analysis (PCA), we consider the problem of determining the number of principal components as a model selection prob...
Zhihua Zhang, Kap Luk Chan, James T. Kwok, Dit-Yan...
PRICAI
2000
Springer
15 years 3 months ago
Generating Hierarchical Structure in Reinforcement Learning from State Variables
This paper presents the CQ algorithm which decomposes and solves a Markov Decision Process (MDP) by automatically generating a hierarchy of smaller MDPs using state variables. The ...
Bernhard Hengst
BMVC
2000
15 years 1 months ago
A Hierarchical Model of Dynamics for Tracking People with a Single Video Camera
We propose a novel hierarchical model of human dynamics for view independent tracking of the human body in monocular video sequences. The model is trained using real data from a c...
I. A. Karaulova, Peter M. Hall, A. David Marshall
TMC
2011
219views more  TMC 2011»
14 years 6 months ago
Optimal Channel Access Management with QoS Support for Cognitive Vehicular Networks
We consider the problem of optimal channel access to provide quality of service (QoS) for data transmission in cognitive vehicular networks. In such a network the vehicular nodes ...
Dusit Niyato, Ekram Hossain, Ping Wang
COLING
2008
15 years 1 months ago
A Syntactic Time-Series Model for Parsing Fluent and Disfluent Speech
This paper describes an incremental approach to parsing transcribed spontaneous speech containing disfluencies with a Hierarchical Hidden Markov Model (HHMM). This model makes use...
Tim Miller, William Schuler