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» Probabilistic Analysis of Large Finite State Machines
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SDM
2012
SIAM
237views Data Mining» more  SDM 2012»
13 years 2 months ago
A Distributed Kernel Summation Framework for General-Dimension Machine Learning
Kernel summations are a ubiquitous key computational bottleneck in many data analysis methods. In this paper, we attempt to marry, for the first time, the best relevant technique...
Dongryeol Lee, Richard W. Vuduc, Alexander G. Gray
77
Voted
STACS
2005
Springer
15 years 5 months ago
Recursive Markov Chains, Stochastic Grammars, and Monotone Systems of Nonlinear Equations
We introduce and study Recursive Markov Chains (RMCs), which extend ordinary finite state Markov chains with the ability to invoke other Markov chains in a potentially recursive m...
Kousha Etessami, Mihalis Yannakakis
QEST
2006
IEEE
15 years 5 months ago
Safe On-The-Fly Steady-State Detection for Time-Bounded Reachability
The time-bounded reachability problem for continuoustime Markov chains (CTMCs) amounts to determine the probability to reach a (set of) goal state(s) within a given time span, suc...
Joost-Pieter Katoen, Ivan S. Zapreev
APL
1992
ACM
15 years 3 months ago
Compiler Tools in APL
We present the design and implementation of APL Intrinsic Functions for a Finite State Machine (also known as a Finite State Automaton) which recognizes regular languages, and a P...
Robert Bernecky, Gert Osterburg
ICML
2007
IEEE
16 years 15 days ago
Local dependent components
We introduce a mixture of probabilistic canonical correlation analyzers model for analyzing local correlations, or more generally mutual statistical dependencies, in cooccurring d...
Arto Klami, Samuel Kaski