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NIPS
2003
15 years 7 months 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
GECCO
2010
Springer
173views Optimization» more  GECCO 2010»
15 years 6 months ago
Superstate identification for state machines using search-based clustering
State machines are a popular method of representing a syshigh level of abstraction that enables developers to gain an overview of the system they represent and quickly understand ...
Mathew Hall, Phil McMinn, Neil Walkinshaw
161
Voted
CIKM
2008
Springer
15 years 8 months ago
Privacy-preserving data publishing for horizontally partitioned databases
There is an increasing need for sharing data repositories containing personal information across multiple distributed, possibly untrusted, and private databases. Such data sharing...
Pawel Jurczyk, Li Xiong
ICDE
2007
IEEE
120views Database» more  ICDE 2007»
16 years 21 days ago
Optimizing State-Intensive Non-Blocking Queries Using Run-time Adaptation
Main memory is a critical resource when processing non-blocking queries with state intensive operators that require real-time responses. While partitioned parallel processing can ...
Bin Liu, Mariana Jbantova, Elke A. Rundensteiner
IAT
2005
IEEE
15 years 12 months ago
Decomposing Large-Scale POMDP Via Belief State Analysis
Partially observable Markov decision process (POMDP) is commonly used to model a stochastic environment with unobservable states for supporting optimal decision making. Computing ...
Xin Li, William K. Cheung, Jiming Liu