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ICANN
2007
Springer
16 years 1 months ago
Structure Learning with Nonparametric Decomposable Models
Abstract. We present a novel approach to structure learning for graphical models. By using nonparametric estimates to model clique densities in decomposable models, both discrete a...
Anton Schwaighofer, Mathäus Dejori, Volker Tr...
VLSID
2003
IEEE
77views VLSI» more  VLSID 2003»
16 years 7 months ago
A Methodology for Accurate Modeling of Energy Dissipation in Array Structures
There is an increasing need for obtaining a reasonably accurate estimate of energy dissipation in SoC designs. Array structures have a significant contribution to the total system...
Mahesh Mamidipaka, Nikil D. Dutt, Kamal S. Khouri
TOOLS
1998
IEEE
15 years 11 months ago
Declarative Reasoning about the Structure of Object-Oriented Systems
The structure of object-oriented systems typically forms a complicated, tangled web of interdependent classes. Understanding this implicit and hidden structure poses severe proble...
Roel Wuyts
CORR
2010
Springer
124views Education» more  CORR 2010»
15 years 4 months ago
Lattice model refinement of protein structures
To find the best lattice model representation of a given full atom protein structure is a hard computational problem. Several greedy methods have been suggested where results are ...
Martin Mann, Alessandro Dal Palù
ICML
2009
IEEE
16 years 8 months ago
Learning structurally consistent undirected probabilistic graphical models
In many real-world domains, undirected graphical models such as Markov random fields provide a more natural representation of the dependency structure than directed graphical mode...
Sushmita Roy, Terran Lane, Margaret Werner-Washbur...