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101
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AAAI
1996
15 years 1 months ago
Sequential Inductive Learning
This article advocates a new model for inductive learning. Called sequential induction, it helps bridge classical fixed-sample learning techniques (which are efficient but difficu...
Jonathan Gratch
126
Voted
NN
2010
Springer
189views Neural Networks» more  NN 2010»
14 years 7 months ago
Sparse kernel learning with LASSO and Bayesian inference algorithm
Kernelized LASSO (Least Absolute Selection and Shrinkage Operator) has been investigated in two separate recent papers (Gao et al., 2008) and (Wang et al., 2007). This paper is co...
Junbin Gao, Paul W. Kwan, Daming Shi
KDD
1994
ACM
96views Data Mining» more  KDD 1994»
15 years 4 months ago
DICE: A Discovery Environment Integrating Inductive Bias
: Most of Knowledge Discovery in Database (KDD) systems are integrating efficient Machine Learning techniques. In fact issues in Machine Learning and KDD are very close allowing fo...
Jean-Daniel Zucker, Vincent Corruble, J. Thomas, G...
109
Voted
CVPR
2012
IEEE
13 years 2 months ago
Discriminately decreasing discriminability with learned image filters
In machine learning and computer vision, input signals are often filtered to increase data discriminability. For example, preprocessing face images with Gabor band-pass filters ...
Jacob Whitehill, Javier R. Movellan
86
Voted
ICML
1989
IEEE
15 years 4 months ago
Constructive Induction by Analogy
The available concept-learners only partially fulfill the needs imposed by the learning apprentice generation of learners. We present a novel approach to interactive concept-learni...
Luc De Raedt, Maurice Bruynooghe