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» Variational nonparametric Bayesian Hidden Markov Model
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UAI
2003
14 years 11 months ago
The Revisiting Problem in Mobile Robot Map Building: A Hierarchical Bayesian Approach
We present an application of hierarchical Bayesian estimation to robot map building. The revisiting problem occurs when a robot has to decide whether it is seeing a previously-bui...
Benjamin Stewart, Jonathan Ko, Dieter Fox, Kurt Ko...
91
Voted
NIPS
2008
14 years 12 months ago
Extracting State Transition Dynamics from Multiple Spike Trains with Correlated Poisson HMM
Neural activity is non-stationary and varies across time. Hidden Markov Models (HMMs) have been used to track the state transition among quasi-stationary discrete neural states. W...
Kentaro Katahira, Jun Nishikawa, Kazuo Okanoya, Ma...
AI
2002
Springer
14 years 10 months ago
The size distribution for Markov equivalence classes of acyclic digraph models
Bayesian networks, equivalently graphical Markov models determined by acyclic digraphs or ADGs (also called directed acyclic graphs or dags), have proved to be both effective and ...
Steven B. Gillispie, Michael D. Perlman
67
Voted
ICIP
2003
IEEE
16 years 1 days ago
Techniques for automatic video content derivation
In this paper, we focus on the use of three different techniques that support automatic derivation of video content from raw video data, namely, a spatio-temporal rule-based metho...
Milan Petkovic, Vojkan Mihajlovic, Willem Jonker
69
Voted
DCC
2010
IEEE
14 years 9 months ago
Neural Markovian Predictive Compression: An Algorithm for Online Lossless Data Compression
This work proposes a novel practical and general-purpose lossless compression algorithm named Neural Markovian Predictive Compression (NMPC), based on a novel combination of Bayesi...
Erez Shermer, Mireille Avigal, Dana Shapira