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ML
2010
ACM
151views Machine Learning» more  ML 2010»
13 years 6 months ago
Inductive transfer for learning Bayesian networks
In several domains it is common to have data from different, but closely related problems. For instance, in manufacturing, many products follow the same industrial process but with...
Roger Luis, Luis Enrique Sucar, Eduardo F. Morales
TMI
2011
127views more  TMI 2011»
13 years 2 months ago
Reconstruction of Large, Irregularly Sampled Multidimensional Images. A Tensor-Based Approach
Abstract—Many practical applications require the reconstruction of images from irregularly sampled data. The spline formalism offers an attractive framework for solving this prob...
Oleksii Vyacheslav Morozov, Michael Unser, Patrick...
IJRR
2010
88views more  IJRR 2010»
13 years 2 months ago
Extracting Object Contours with the Sweep of a Robotic Whisker Using Torque Information
Several recent studies have investigated the problem of object feature extraction with artificial whiskers. Many of these studies have used an approach in which the whisker is rot...
Joseph H. Solomon, Mitra J. Z. Hartmann
JUCS
2010
109views more  JUCS 2010»
13 years 2 months ago
Semantics of Query-Driven Communication of Exact Values
: We address the question of how to communicate among distributed processes values such as real numbers, continuous functions and geometrical solids with arbitrary precision, yet e...
Michal Konecný, Amin Farjudian
CVPR
2000
IEEE
14 years 9 months ago
Improving Visual Matching
Many visual matching algorithms can be described in terms of the features and the inter-feature distance or metric. The most commonly used metric is the sum of squared di erences ...
Michael S. Lew, Nicu Sebe, Thomas S. Huang