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» Reformulating Constraint Models Using Input Data
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BMCBI
2005
88views more  BMCBI 2005»
14 years 9 months ago
Using large-scale perturbations in gene network reconstruction
Background: Recent analysis of the yeast gene network shows that most genes have few inputs, indicating that enumerative gene reconstruction methods are both useful and computatio...
Thomas MacCarthy, Andrew Pomiankowski, Robert Seym...
CDC
2009
IEEE
133views Control Systems» more  CDC 2009»
15 years 2 months ago
A symbolic model approach to the digital control of nonlinear time-delay systems
— In this paper we propose an approach to control design of nonlinear time–delay systems, which is based on the construction of symbolic models, where each symbolic state and e...
Giordano Pola, Pierdomenico Pepe, Maria Domenica D...
FOSAD
2009
Springer
15 years 4 months ago
The Open-Source Fixed-Point Model Checker for Symbolic Analysis of Security Protocols
We introduce the Open-source Fixed-point Model Checker OFMC for symbolic security protocol analysis, which extends the Onthe-fly Model Checker (the previous OFMC). The native inpu...
Sebastian Mödersheim, Luca Viganò
SIGIR
2006
ACM
15 years 3 months ago
Unifying user-based and item-based collaborative filtering approaches by similarity fusion
Memory-based methods for collaborative filtering predict new ratings by averaging (weighted) ratings between, respectively, pairs of similar users or items. In practice, a large ...
Jun Wang, Arjen P. de Vries, Marcel J. T. Reinders
ICASSP
2011
IEEE
14 years 1 months ago
Deep Belief Networks using discriminative features for phone recognition
Deep Belief Networks (DBNs) are multi-layer generative models. They can be trained to model windows of coefficients extracted from speech and they discover multiple layers of fea...
Abdel-rahman Mohamed, Tara N. Sainath, George Dahl...