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» Comparison of Clique-Listing Algorithms
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CLEF
2010
Springer
15 years 1 months ago
FastDocode: Finding Approximated Segments of N-Grams for Document Copy Detection - Lab Report for PAN at CLEF 2010
Nowadays, plagiarism has been presented as one of the main distresses that the information technology revolution has lead into our society for which using pattern matching algorith...
Gabriel Oberreuter, Gaston L'Huillier, Sebasti&aac...
PAMI
2011
15 years 1 months ago
Semi-Supervised Learning via Regularized Boosting Working on Multiple Semi-Supervised Assumptions
—Semi-supervised learning concerns the problem of learning in the presence of labeled and unlabeled data. Several boosting algorithms have been extended to semi-supervised learni...
Ke Chen, Shihai Wang
ICASSP
2011
IEEE
14 years 10 months ago
Iterative estimation of structures of multiple RNA homologs: Turbofold
TurboFold, an iterative algorithm for estimating the common secondary structures of multiple RNA homologs, is presented. The algorithm is motivated by and has structure and attrib...
Gaurav Sharma, Arif Ozgun Harmanci, David H. Mathe...
CVPR
2012
IEEE
13 years 9 months ago
Changedetection.net: A new change detection benchmark dataset
Change detection is one of the most commonly encountered low-level tasks in computer vision and video processing. A plethora of algorithms have been developed to date, yet no wide...
Nil Goyette, Pierre-Marc Jodoin, Fatih Porikli, Ja...
ICONIP
2004
15 years 8 months ago
The Most Robust Loss Function for Boosting
Boosting algorithm is understood as the gradient descent algorithm of a loss function. It is often pointed out that the typical boosting algorithm, Adaboost, is seriously affected ...
Takafumi Kanamori, Takashi Takenouchi, Shinto Eguc...