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ASPDAC
1999
ACM
144views Hardware» more  ASPDAC 1999»
15 years 1 months ago
Model Order Reduction of Large Circuits Using Balanced Truncation
A method is introduced for model order reduction of large circuits extracted from layout. The algorithm, which is based on balanced realization, can be used for reducing the order ...
Payam Rabiei, Massoud Pedram
81
Voted
FAW
2008
Springer
111views Algorithms» more  FAW 2008»
14 years 11 months ago
Efficient First-Order Model-Checking Using Short Labels
We prove that there exists an O(log(n))-labeling scheme for every first-order formula with free set variables in every class of graphs that is nicely locally cwd-decomposable, whic...
Bruno Courcelle, Cyril Gavoille, Mamadou Moustapha...
ICCAD
2006
IEEE
165views Hardware» more  ICCAD 2006»
15 years 6 months ago
A fast block structure preserving model order reduction for inverse inductance circuits
Most existing RCL−1 circuit reductions stamp inverse inductance L−1 elements by a second-order nodal analysis (NA). The NA formulation uses nodal voltage variables and describ...
Hao Yu, Yiyu Shi, Lei He, David Smart
DAGM
2010
Springer
14 years 10 months ago
Gaussian Mixture Modeling with Gaussian Process Latent Variable Models
Density modeling is notoriously difficult for high dimensional data. One approach to the problem is to search for a lower dimensional manifold which captures the main characteristi...
Hannes Nickisch, Carl Edward Rasmussen
97
Voted

Publication
404views
15 years 6 months ago
Bayesian variable order Markov models.
We present a simple, effective generalisation of variable order Markov models to full online Bayesian estimation. The mechanism used is close to that employed in context tree wei...
Christos Dimitrakakis