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SIGIR
2006
ACM
16 years 9 days ago
Large scale semi-supervised linear SVMs
Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In...
Vikas Sindhwani, S. Sathiya Keerthi
INFOVIS
2005
IEEE
15 years 12 months ago
PRISAD: A Partitioned Rendering Infrastructure for Scalable Accordion Drawing
We present PRISAD, the first generic rendering infrastructure for information visualization applications that use the accordion drawing technique: rubber-sheet navigation with gu...
James Slack, Kristian Hildebrand, Tamara Munzner
VISUALIZATION
2005
IEEE
15 years 12 months ago
Query-Driven Visualization of Large Data Sets
We present a practical and general-purpose approach to large and complex visual data analysis where visualization processing, rendering and subsequent human interpretation is cons...
Kurt Stockinger, John Shalf, Kesheng Wu, E. Wes Be...
BIRTHDAY
2005
Springer
15 years 12 months ago
Planning in Answer Set Programming using Ordered Task Decomposition
abstract. In this paper we investigate a formalism for solving planning problems based on ordered task decomposition using Answer Set Programming (ASP). Our planning methodology is...
Jürgen Dix, Ugur Kuter, Dana S. Nau
GECCO
2005
Springer
232views Optimization» more  GECCO 2005»
15 years 12 months ago
A hardware pipeline for function optimization using genetic algorithms
Genetic Algorithms (GAs) are very commonly used as function optimizers, basically due to their search capability. A number of different serial and parallel versions of GA exist. ...
Malay Kumar Pakhira, Rajat K. De