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JMLR
2010
157views more  JMLR 2010»
14 years 4 months ago
Why are DBNs sparse?
Real stochastic processes operating in continuous time can be modeled by sets of stochastic differential equations. On the other hand, several popular model families, including hi...
Shaunak Chatterjee, Stuart Russell
IPMU
2010
Springer
15 years 2 months ago
Independent Natural Extension
We introduce a general definition for the independence of a number of finite-valued variables, based on coherent lower previsions. Our definition has an epistemic flavour: it a...
Gert de Cooman, Enrique Miranda, Marco Zaffalon
IJCNN
2006
IEEE
15 years 4 months ago
Training of Large-Scale Feed-Forward Neural Networks
Abstract— Neural processing of large-scale data sets containing both many input / output variables and a large number of training examples often leads to very large networks. Onc...
Udo Seiffert
IPMU
2010
Springer
14 years 12 months ago
On Nonparametric Predictive Inference for Ordinal Data
Abstract. Nonparametric predictive inference (NPI) is a powerful frequentist statistical framework based only on an exchangeability assumption for future and past observations, mad...
Frank P. A. Coolen, Pauline Coolen-Schrijner, Taha...
ACL
2004
14 years 11 months ago
Unsupervised Sense Disambiguation Using Bilingual Probabilistic Models
We describe two probabilistic models for unsupervised word-sense disambiguation using parallel corpora. The first model, which we call the Sense model, builds on the work of Diab ...
Indrajit Bhattacharya, Lise Getoor, Yoshua Bengio