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JMLR
2010
155views more  JMLR 2010»
15 years 3 months ago
Approximate Tree Kernels
Convolution kernels for trees provide simple means for learning with tree-structured data. The computation time of tree kernels is quadratic in the size of the trees, since all pa...
Konrad Rieck, Tammo Krueger, Ulf Brefeld, Klaus-Ro...
129
Voted
TMI
2010
133views more  TMI 2010»
15 years 3 months ago
Synthetic Magnetic Resonance Imaging Revisited
—Synthetic magnetic resonance (MR) imaging is an approach suggested in the literature to predict MR images at different design parameter settings from at least three observed MR ...
Ranjan Maitra, John J. Riddles
JMLR
2010
144views more  JMLR 2010»
14 years 12 months ago
Maximum Margin Learning with Incomplete Data: Learning Networks instead of Tables
In this paper we address the problem of predicting when the available data is incomplete. We show that changing the generally accepted table-wise view of the sample items into a g...
Sándor Szedmák, Yizhao Ni, Steve R. ...
CVPR
2009
IEEE
1942views Computer Vision» more  CVPR 2009»
17 years 18 days ago
Learning Similarity Measure for Multi-Modal 3D Image Registration
Multi-modal image registration is a challenging problem in medical imaging. The goal is to align anatomically identical structures; however, their appearance in images acquired wit...
Bernhard Schölkopf, Daewon Lee, Florian Stein...
DAC
1999
ACM
16 years 6 months ago
Synthesis of Embedded Software Using Free-Choice Petri Nets
Software synthesis from a concurrent functional specification is a key problem in the design of embedded systems. A concurrent specification is well-suited for medium-grained part...
Marco Sgroi, Luciano Lavagno