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AAAI
1996
15 years 6 months ago
A Hybrid Learning Approach for Better Recognition of Visual Objects
Real world images often contain similar objects but with different rotations, noise, or other visual alterations. Vision systems should be able to recognize objects regardless of ...
Ibrahim F. Imam, Srinivas Gutta
PAMI
2006
114views more  PAMI 2006»
15 years 4 months ago
Nonparametric Supervised Learning by Linear Interpolation with Maximum Entropy
Nonparametric neighborhood methods for learning entail estimation of class conditional probabilities based on relative frequencies of samples that are "near-neighbors" of...
Maya R. Gupta, Robert M. Gray, Richard A. Olshen
111
Voted
PR
2006
89views more  PR 2006»
15 years 4 months ago
Gaussian fields for semi-supervised regression and correspondence learning
Gaussian fields (GF) have recently received considerable attention for dimension reduction and semi-supervised classification. In this paper we show how the GF framework can be us...
Jakob J. Verbeek, Nikos A. Vlassis
IJCSS
2007
122views more  IJCSS 2007»
15 years 4 months ago
Artificial Neural Network Type Learning with Single Multiplicative Spiking Neuron
In this paper, learning algorithm for a single multiplicative spiking neuron (MSN) is proposed and tested for various applications where a multilayer perceptron (MLP) neural netwo...
Deepak Mishra, Abhishek Yadav, Sudipta Ray, Prem K...
CORR
2000
Springer
134views Education» more  CORR 2000»
15 years 4 months ago
Learning Complexity Dimensions for a Continuous-Time Control System
This paper takes a computational learning theory approach to a problem of linear systems identification. It is assumed that inputs are generated randomly from a known class consist...
Pirkko Kuusela, Daniel Ocone, Eduardo D. Sontag