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RAS
2008
112views more  RAS 2008»
15 years 6 months ago
Learning and generalising semantic knowledge from object scenes
The robot described in this paper learns words that relate to objects and their attributes and also learns concepts, which may be recursive, that involve relationships between sev...
Claire D'Este, Claude Sammut
ICASSP
2009
IEEE
15 years 4 months ago
Target detection using incremental learning on single-trial evoked response
The human neural responses associated with cognitive events, referred as event related potentials (ERPs), can provide reliable inference for target image detection. Incremental le...
Yonghong Huang, Deniz Erdogmus, Misha Pavel, Kenne...
IR
2011
15 years 1 months ago
Learning to rank for why-question answering
In this paper, we evaluate a number of machine learning techniques for the task of ranking answers to why-questions. We use TF-IDF together with a set of 36 linguistically motivate...
Suzan Verberne, Hans van Halteren, Daphne Theijsse...
DMIN
2008
190views Data Mining» more  DMIN 2008»
15 years 8 months ago
Optimization of Self-Organizing Maps Ensemble in Prediction
The knowledge discovery process encounters the difficulties to analyze large amount of data. Indeed, some theoretical problems related to high dimensional spaces then appear and de...
Elie Prudhomme, Stéphane Lallich
ICML
2004
IEEE
16 years 7 months ago
K-means clustering via principal component analysis
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
Chris H. Q. Ding, Xiaofeng He