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» Set cover algorithms for very large datasets
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ICPR
2000
IEEE
15 years 11 months ago
Automatic Training of Page Segmentation Algorithms: An Optimization Approach
Most page segmentation algorithms have userspecifiable free parameters. However, algorithm designers typically do not provide a quantitative/rigorous method for choosing values fo...
Song Mao, Tapas Kanungo
VLDB
2004
ACM
186views Database» more  VLDB 2004»
15 years 3 months ago
Indexing Large Human-Motion Databases
Data-driven animation has become the industry standard for computer games and many animated movies and special effects. In particular, motion capture data recorded from live actor...
Eamonn J. Keogh, Themis Palpanas, Victor B. Zordan...
NDSS
2009
IEEE
15 years 4 months ago
Coordinated Scan Detection
Coordinated attacks, where the tasks involved in an attack are distributed amongst multiple sources, can be used by an adversary to obfuscate his incursion. In this paper we prese...
Carrie Gates
ALGORITHMICA
2006
77views more  ALGORITHMICA 2006»
14 years 9 months ago
Scalable Parallel Algorithms for FPT Problems
Algorithmic methods based on the theory of fixed-parameter tractability are combined with powerful computational platforms to launch systematic attacks on combinatorial problems o...
Faisal N. Abu-Khzam, Michael A. Langston, Pushkar ...
ICPR
2010
IEEE
15 years 6 days ago
Fast Training of Object Detection Using Stochastic Gradient Descent
Training datasets for object detection problems are typically very large and Support Vector Machine (SVM) implementations are computationally complex. As opposed to these complex ...
Rob Wijnhoven, Peter H. N. De With