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» Approximate algorithms for neural-Bayesian approaches
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ECML
2006
Springer
15 years 1 months ago
PAC-Learning of Markov Models with Hidden State
The standard approach for learning Markov Models with Hidden State uses the Expectation-Maximization framework. While this approach had a significant impact on several practical ap...
Ricard Gavaldà, Philipp W. Keller, Joelle P...
VVS
2000
IEEE
126views Visualization» more  VVS 2000»
15 years 1 months ago
Time critical isosurface refinement and smoothing
Multi-resolution data-structures and algorithms are key in Visualization to achieve real-time interaction with large data-sets. Research has been primarily focused on the off-line...
Valerio Pascucci, Chandrajit L. Bajaj
ASPDAC
2008
ACM
200views Hardware» more  ASPDAC 2008»
14 years 12 months ago
Non-Gaussian statistical timing analysis using second-order polynomial fitting
In the nanometer manufacturing region, process variation causes significant uncertainty for circuit performance verification. Statistical static timing analysis (SSTA) is thus dev...
Lerong Cheng, Jinjun Xiong, Lei He
DAWAK
2008
Springer
14 years 11 months ago
Mining Multidimensional Sequential Patterns over Data Streams
Sequential pattern mining is an active field in the domain of knowledge discovery and has been widely studied for over a decade by data mining researchers. More and more, with the ...
Chedy Raïssi, Marc Plantevit
CORR
2010
Springer
89views Education» more  CORR 2010»
14 years 10 months ago
Distributed Control of the Laplacian Spectral Moments of a Network
It is well-known that the eigenvalue spectrum of the Laplacian matrix of a network contains valuable information about the network structure and the behavior of many dynamical proc...
Victor M. Preciado, Michael M. Zavlanos, Ali Jadba...