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NIPS
1997
15 years 8 months ago
Learning Generative Models with the Up-Propagation Algorithm
Up-propagation is an algorithm for inverting and learning neural network generative models. Sensory input is processed by inverting a model that generates patterns from hidden var...
Jong-Hoon Oh, H. Sebastian Seung
PR
2010
147views more  PR 2010»
15 years 5 months ago
Minimum classification error learning for sequential data in the wavelet domain
Wavelet analysis has found widespread use in signal processing and many classification tasks. Nevertheless, its use in dynamic pattern recognition have been much more restricted ...
D. Tomassi, Diego H. Milone, L. Forzani
ICDAR
1997
IEEE
15 years 10 months ago
Modeling Documents for Structure Recognition Using Generalized N-Grams
In this paper we present and discuss a novel approach to modeling logical structures of documents, based on a statistical representation of patterns in a document class. An effic...
Rolf Brugger, Abdel Wahab Zramdini, Rolf Ingold
IEAAIE
2011
Springer
14 years 10 months ago
A Cognitive Agent Model Using Inverse Mirroring for False Attribution of Own Actions to Other Agents
This paper presents a cognitive agent model capable of showing situations where self-generated actions are attributed to other agents, as, for example, for patients suffering from ...
Jan Treur, Muhammad Umair
ICPR
2002
IEEE
16 years 7 months ago
Learning Bayesian Network Classifiers for Credit Scoring Using Markov Chain Monte Carlo Search
In this paper, we will evaluate the power and usefulness of Bayesian network classifiers for credit scoring. Various types of Bayesian network classifiers will be evaluated and co...
Bart Baesens, Michael Egmont-Petersen, Robert Cast...