Sciweavers

702 search results - page 84 / 141
» Learning Probabilistic Models of Relational Structure
Sort
View
IJCAI
2003
15 years 1 months ago
Hierarchical Hidden Markov Models for Information Extraction
Information extraction can be defined as the task of automatically extracting instances of specified classes or relations from text. We consider the case of using machine learni...
Marios Skounakis, Mark Craven, Soumya Ray
NIPS
1998
15 years 1 months ago
An Entropic Estimator for Structure Discovery
We introduce a novel framework for simultaneous structure and parameter learning in hidden-variable conditional probability models, based on an entropic prior and a solution for i...
Matthew Brand
AUSAI
2008
Springer
15 years 2 months ago
Character Recognition Using Hierarchical Vector Quantization and Temporal Pooling
In recent years, there has been a cross-fertilization of ideas between computational neuroscience models of the operation of the neocortex and artificial intelligence models of mac...
John Thornton, Jolon Faichney, Michael Blumenstein...
IJCNN
2006
IEEE
15 years 6 months ago
Patterns, Hypergraphs and Embodied General Intelligence
—It is proposed that the creation of Artificial General Intelligence (AGI) at the human level and ultimately beyond is a problem addressable via integrating computer science algo...
Ben Goertzel
GECCO
2008
Springer
135views Optimization» more  GECCO 2008»
15 years 1 months ago
iBOA: the incremental bayesian optimization algorithm
This paper proposes the incremental Bayesian optimization algorithm (iBOA), which modifies standard BOA by removing the population of solutions and using incremental updates of t...
Martin Pelikan, Kumara Sastry, David E. Goldberg