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» Learning Classifiers from Semantically Heterogeneous Data
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IJCAI
2007
13 years 11 months ago
Parametric Kernels for Sequence Data Analysis
A key challenge in applying kernel-based methods for discriminative learning is to identify a suitable kernel given a problem domain. Many methods instead transform the input data...
Young-In Shin, Donald S. Fussell
IJRR
2010
214views more  IJRR 2010»
13 years 7 months ago
Object Recognition in 3D Point Clouds Using Web Data and Domain Adaptation
Over the last years, object detection has become a more and more active field of research in robotics. An important problem in object detection is the need for sufficient labeled ...
Kevin Lai, Dieter Fox
SEMWEB
2009
Springer
14 years 4 months ago
Populating the Semantic Web by Macro-reading Internet Text
A key question regarding the future of the semantic web is “how will we acquire structured information to populate the semantic web on a vast scale?” One approach is to enter t...
Tom M. Mitchell, Justin Betteridge, Andrew Carlson...
RECOMB
2006
Springer
14 years 10 months ago
Improving Prediction of Zinc Binding Sites by Modeling the Linkage Between Residues Close in Sequence
Abstract. We describe and empirically evaluate machine learning methods for the prediction of zinc binding sites from protein sequences. We start by observing that a data set consi...
Sauro Menchetti, Andrea Passerini, Paolo Frasconi,...
CORR
2007
Springer
164views Education» more  CORR 2007»
13 years 10 months ago
Consistency of the group Lasso and multiple kernel learning
We consider the least-square regression problem with regularization by a block 1-norm, that is, a sum of Euclidean norms over spaces of dimensions larger than one. This problem, r...
Francis Bach