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» The complexity of approximating entropy
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ICML
2004
IEEE
16 years 7 months ago
Learning associative Markov networks
Markov networks are extensively used to model complex sequential, spatial, and relational interactions in fields as diverse as image processing, natural language analysis, and bio...
Benjamin Taskar, Vassil Chatalbashev, Daphne Kolle...
VLSID
2002
IEEE
91views VLSI» more  VLSID 2002»
16 years 7 months ago
Rational ABCD Modeling of High-Speed Interconnects
This paper introduces a new numerical approximation technique, called the Differential Quadrature Method (DQM), in order to derive the rational ABCD matrix representing the high-s...
Qinwei Xu, Pinaki Mazumder
QEST
2009
IEEE
16 years 1 months ago
Comparison of Two Output Models for the BMAP/MAP/1 Departure Process
—The departure process of a BMAP/MAP/1 queue can be approximated in different ways: as a Markovian arrival process (MAP) or as a matrix-exponential process (MEP). Both approximat...
Qi Zhang, Armin Heindl, Evgenia Smirni, Andreas St...
GECCO
2009
Springer
16 years 1 months ago
On the scalability of XCS(F)
Many successful applications have proven the potential of Learning Classifier Systems and the XCS classifier system in particular in datamining, reinforcement learning, and func...
Patrick O. Stalph, Martin V. Butz, David E. Goldbe...
CSFW
2007
IEEE
16 years 28 days ago
Compositional Security for Task-PIOAs
Task-PIOA is a modeling framework for distributed systems with both probabilistic and nondeterministic behaviors. It is suitable for cryptographic applications because its task-bas...
Ran Canetti, Ling Cheung, Dilsun Kirli Kaynar, Nan...