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» Passage time distributions in large Markov chains
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ACL
1994
14 years 11 months ago
A Markov Language Learning Model for Finite Parameter Spaces
This paper shows how to formally characterize language learning in a finite parameter space as a Markov structure, hnportant new language learning results follow directly: explici...
Partha Niyogi, Robert C. Berwick
NIPS
2004
14 years 11 months ago
Incremental Learning for Visual Tracking
Most existing tracking algorithms construct a representation of a target object prior to the tracking task starts, and utilize invariant features to handle appearance variation of...
Jongwoo Lim, David A. Ross, Ruei-Sung Lin, Ming-Hs...
SODA
2008
ACM
122views Algorithms» more  SODA 2008»
14 years 11 months ago
Fast approximation of the permanent for very dense problems
Approximation of the permanent of a matrix with nonnegative entries is a well studied problem. The most successful approach to date for general matrices uses Markov chains to appr...
Mark Huber, Jenny Law
QEST
2005
IEEE
15 years 3 months ago
iLTLChecker: A Probabilistic Model Checker for Multiple DTMCs
iLTL is a probabilistic temporal logic that can specify properties of multiple discrete time Markov chains (DTMCs). In this paper, we describe two related tools: MarkovEstimator a...
YoungMin Kwon, Gul A. Agha
QEST
2007
IEEE
15 years 4 months ago
A Generic Mean Field Convergence Result for Systems of Interacting Objects
We consider a model for interacting objects, where the evolution of each object is given by a finite state Markov chain, whose transition matrix depends on the present and the pa...
Jean-Yves Le Boudec, David McDonald, Jochen Mundin...