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» Cosparse analysis modeling - uniqueness and algorithms
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159
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3DIM
2011
IEEE
14 years 3 months ago
A Non-cooperative Game for 3D Object Recognition in Cluttered Scenes
Abstract—During the last few years a wide range of algorithms and devices have been made available to easily acquire range images. To this extent, the increasing abundance of dep...
Andrea Albarelli, Emanuele Rodolà, Filippo ...
KDD
2012
ACM
207views Data Mining» more  KDD 2012»
13 years 6 months ago
Robust multi-task feature learning
Multi-task learning (MTL) aims to improve the performance of multiple related tasks by exploiting the intrinsic relationships among them. Recently, multi-task feature learning alg...
Pinghua Gong, Jieping Ye, Changshui Zhang
GECCO
2006
Springer
179views Optimization» more  GECCO 2006»
15 years 7 months ago
Parisian evolution with honeybees for three-dimensional reconstruction
This paper introduces a novel analogy with the way in which honeybee colonies operate in order to solve the problem of sparse and quasi dense reconstruction. To successfully solve...
Gustavo Olague, Cesar Puente
126
Voted
GFKL
2006
Springer
78views Data Mining» more  GFKL 2006»
15 years 7 months ago
Putting Successor Variety Stemming to Work
Stemming algorithms find canonical forms for inflected words, e. g. for declined nouns or conjugated verbs. Since such a unification of words with respect to gender, number, time, ...
Benno Stein, Martin Potthast
127
Voted
IFIP12
2007
15 years 5 months ago
Clustering Improves the Exploration of Graph Mining Results
Mining frequent subgraphs is an area of research where we have a given set of graphs, and where we search for (connected) subgraphs contained in many of these graphs. Each graph ca...
Edgar H. de Graaf, Joost N. Kok, Walter A. Kosters