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NIPS
2003
14 years 9 days ago
Inferring State Sequences for Non-linear Systems with Embedded Hidden Markov Models
We describe a Markov chain method for sampling from the distribution of the hidden state sequence in a non-linear dynamical system, given a sequence of observations. This method u...
Radford M. Neal, Matthew J. Beal, Sam T. Roweis
UAI
1996
14 years 8 days ago
A Qualitative Markov Assumption and Its Implications for Belief Change
The study of belief change has been an active area in philosophy and AI. In recent years, two special cases of belief change, belief revision and belief update, have been studied ...
Nir Friedman, Joseph Y. Halpern
GIS
2010
ACM
13 years 9 months ago
Querying the future of spatio-temporal objects
Since navigation systems and tracking devices are becoming ubiquitous in our daily life, the development of efficient methods for processing massive sets of mobile objects are of ...
Philip Schmiegelt, Bernhard Seeger
JAIR
2011
133views more  JAIR 2011»
13 years 6 months ago
A Probabilistic Approach for Maintaining Trust Based on Evidence
Leading agent-based trust models address two important needs. First, they show how an agent may estimate the trustworthiness of another agent based on prior interactions. Second, ...
Yonghong Wang, Chung-Wei Hang, Munindar P. Singh
AI
2006
Springer
13 years 11 months ago
Controlled generation of hard and easy Bayesian networks: Impact on maximal clique size in tree clustering
This article presents and analyzes algorithms that systematically generate random Bayesian networks of varying difficulty levels, with respect to inference using tree clustering. ...
Ole J. Mengshoel, David C. Wilkins, Dan Roth