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129
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COLT
2008
Springer
15 years 5 months ago
Learning Coordinate Gradients with Multi-Task Kernels
Coordinate gradient learning is motivated by the problem of variable selection and determining variable covariation. In this paper we propose a novel unifying framework for coordi...
Yiming Ying, Colin Campbell
118
Voted
ECML
1994
Springer
15 years 7 months ago
Industrial Applications of ML: Illustrations for the KAML Dilemma and the CBR Dream
This paperpresents several industrial applications of MLin the context of their effort to solve the "KAMLproblem", i.e., the problem of merging knowledge acquisition and...
Yves Kodratoff
115
Voted
ICML
2010
IEEE
15 years 1 months ago
Approximate Predictive Representations of Partially Observable Systems
We provide a novel view of learning an approximate model of a partially observable environment from data and present a simple implemenf the idea. The learned model abstracts away ...
Monica Dinculescu, Doina Precup
157
Voted
PAA
2010
15 years 2 months ago
Exploiting visual and text features for direct marketing learning in time and space constrained domains
Traditionally, direct marketing companies have relied on pre-testing to select the best offers to send to their audiences. Companies systematically dispatch the offers under consid...
Sebastiano Battiato, Giovanni Maria Farinella, Gio...
178
Voted
VIP
2003
15 years 5 months ago
Using Dual Cascading Learning Frameworks for Image Indexing
To bridge the semantic gap in content-based image retrieval, detecting meaningful visual entities (e.g. faces, sky, foliage, buildings etc) in image content and classifying images...
Joo-Hwee Lim, Jesse S. Jin