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» Termination Analysis with Algorithmic Learning
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TCS
2008
14 years 9 months ago
Using bisimulation proof techniques for the analysis of distributed abstract machines
Analysis of Distributed Abstract Machines Damien Pous ENS Lyon, France. We illustrate the use of recently developed proof techniques for weak bisimulation sing a generic framework...
Damien Pous
116
Voted
DAC
1994
ACM
15 years 1 months ago
Probabilistic Analysis of Large Finite State Machines
Regarding nite state machines as Markov chains facilitates the application of probabilistic methods to very large logic synthesis and formal veri cation problems. Recently, we ha...
Gary D. Hachtel, Enrico Macii, Abelardo Pardo, Fab...
ESANN
2004
14 years 11 months ago
A New Learning Rates Adaptation Strategy for the Resilient Propagation Algorithm
In this paper we propose an Rprop modification that builds on a mathematical framework for the convergence analysis to equip Rprop with a learning rates adaptation strategy that en...
Aristoklis D. Anastasiadis, George D. Magoulas, Mi...
CORR
2010
Springer
96views Education» more  CORR 2010»
14 years 9 months ago
Learning High-Dimensional Markov Forest Distributions: Analysis of Error Rates
The problem of learning forest-structured discrete graphical models from i.i.d. samples is considered. An algorithm based on pruning of the Chow-Liu tree through adaptive threshol...
Vincent Y. F. Tan, Animashree Anandkumar, Alan S. ...
IJON
2007
99views more  IJON 2007»
14 years 9 months ago
A relative trust-region algorithm for independent component analysis
In this paper we present a method of parameter optimization, relative trust-region learning, where the trust-region method and the relative optimization [21] are jointly exploited...
Heeyoul Choi, Seungjin Choi