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» Learning Classifiers from Semantically Heterogeneous Data
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JMLR
2010
154views more  JMLR 2010»
13 years 5 months ago
MOA: Massive Online Analysis
Massive Online Analysis (MOA) is a software environment for implementing algorithms and running experiments for online learning from evolving data streams. MOA includes a collecti...
Albert Bifet, Geoff Holmes, Richard Kirkby, Bernha...
MICCAI
2009
Springer
14 years 11 months ago
MKL for Robust Multi-modality AD Classification
We study the problem of classifying mild Alzheimer's disease (AD) subjects from healthy individuals (controls) using multi-modal image data, to facilitate early identification...
Chris Hinrichs, Vikas Singh, Guofan Xu, Sterlin...
GW
2003
Springer
137views Biometrics» more  GW 2003»
14 years 3 months ago
Gestural Mind Markers in ECAs
We aim at creating Embodied Conversational Agents (ECAs) able to communicate multimodally with a user or with other ECAs. In this paper we focus on the Gestural Mind Markers, that ...
Isabella Poggi, Catherine Pelachaud, Emanuela Magn...
JMLR
2006
123views more  JMLR 2006»
13 years 10 months ago
Adaptive Prototype Learning Algorithms: Theoretical and Experimental Studies
In this paper, we propose a number of adaptive prototype learning (APL) algorithms. They employ the same algorithmic scheme to determine the number and location of prototypes, but...
Fu Chang, Chin-Chin Lin, Chi-Jen Lu
BMCBI
2006
134views more  BMCBI 2006»
13 years 10 months ago
Application of machine learning in SNP discovery
Background: Single nucleotide polymorphisms (SNP) constitute more than 90% of the genetic variation, and hence can account for most trait differences among individuals in a given ...
Lakshmi K. Matukumalli, John J. Grefenstette, Davi...