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NN
1997
Springer
174views Neural Networks» more  NN 1997»
15 years 3 months ago
Learning Dynamic Bayesian Networks
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
Zoubin Ghahramani
ECAI
1994
Springer
15 years 3 months ago
Concept Language with Number Restrictions and Fixpoints, and its Relationship with Mu-calculus
Abstract. Many recent works point out that there are several possibilities of assigning a meaning to a concept definition containing some sort of recursion. In this paper, we argue...
Giuseppe De Giacomo, Maurizio Lenzerini
CIDM
2007
IEEE
15 years 3 months ago
Efficient Kernel-based Learning for Trees
Kernel methods are effective approaches to the modeling of structured objects in learning algorithms. Their major drawback is the typically high computational complexity of kernel ...
Fabio Aiolli, Giovanni Da San Martino, Alessandro ...
EVOW
2009
Springer
15 years 3 months ago
A Hierarchical Classification Ant Colony Algorithm for Predicting Gene Ontology Terms
Abstract. This paper proposes a novel Ant Colony Optimisation algorithm for the hierarchical problem of predicting protein functions using the Gene Ontology (GO). The GO structure ...
Fernando E. B. Otero, Alex Alves Freitas, Colin G....
GECCO
2006
Springer
155views Optimization» more  GECCO 2006»
15 years 3 months ago
Comparison of genetic representation schemes for scheduling soft real-time parallel applications
This paper presents a hybrid technique that combines List Scheduling (LS) with Genetic Algorithms (GA) for constructing non-preemptive schedules for soft real-time parallel applic...
Yoginder S. Dandass, Amit C. Bugde