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PRL
2011
15 years 1 months ago
Efficient approximate Regularized Least Squares by Toeplitz matrix
Machine Learning based on the Regularized Least Square (RLS) model requires one to solve a system of linear equations. Direct-solution methods exhibit predictable complexity and s...
Sergio Decherchi, Paolo Gastaldo, Rodolfo Zunino
ICML
1998
IEEE
16 years 7 months ago
Bayesian Network Classification with Continuous Attributes: Getting the Best of Both Discretization and Parametric Fitting
In a recent paper, Friedman, Geiger, and Goldszmidt [8] introduced a classifier based on Bayesian networks, called Tree Augmented Naive Bayes (TAN), that outperforms naive Bayes a...
Moisés Goldszmidt, Nir Friedman, Thomas J. ...
IJCV
2007
159views more  IJCV 2007»
15 years 6 months ago
Face Hallucination: Theory and Practice
In this paper, we study face hallucination, or synthesizing a high-resolution face image from an input low-resolution image, with the help of a large collection of other high-reso...
Ce Liu, Heung-Yeung Shum, William T. Freeman
AIIA
2009
Springer
16 years 1 months ago
Relational Temporal Data Mining for Wireless Sensor Networks
Wireless sensor networks (WSNs) represent a typical domain where there are complex temporal sequences of events. In this paper we propose a relational framework to model and analys...
Teresa Maria Altomare Basile, Nicola Di Mauro, Ste...
BC
2006
105views more  BC 2006»
15 years 6 months ago
A stochastic population approach to the problem of stable recruitment hierarchies in spiking neural networks
Recruitment learning in hierarchies is an inherently unstable process (Valiant, 1994). This paper presents conditions on parameters for a feedforward network to ensure stable recru...
Cengiz Günay, Anthony S. Maida