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» Approximation Algorithms for Clustering Problems
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CAD
2006
Springer
15 years 6 months ago
Cone spline approximation via fat conic spline fitting
Fat conic section and fat conic spline are defined. With well established properties of fat conic splines, the problem of approximating a ruled surface by a tangent smooth cone sp...
Xunnian Yang, Weiping Yang
GIS
2006
ACM
16 years 7 months ago
Computing longest duration flocks in trajectory data
Moving point object data can be analyzed through the discovery of patterns. We consider the computational efficiency of computing two of the most basic spatio-temporal patterns in...
Joachim Gudmundsson, Marc J. van Kreveld
STOC
2007
ACM
181views Algorithms» more  STOC 2007»
16 years 7 months ago
How to rank with few errors
We present a polynomial time approximation scheme (PTAS) for the minimum feedback arc set problem on tournaments. A simple weighted generalization gives a PTAS for KemenyYoung ran...
Claire Kenyon-Mathieu, Warren Schudy
JMLR
2010
130views more  JMLR 2010»
15 years 1 months ago
MOA: Massive Online Analysis, a Framework for Stream Classification and Clustering
Massive Online Analysis (MOA) is a software environment for implementing algorithms and running experiments for online learning from evolving data streams. MOA is designed to deal...
Albert Bifet, Geoff Holmes, Bernhard Pfahringer, P...
ICML
2005
IEEE
16 years 7 months ago
Learning as search optimization: approximate large margin methods for structured prediction
Mappings to structured output spaces (strings, trees, partitions, etc.) are typically learned using extensions of classification algorithms to simple graphical structures (eg., li...
Daniel Marcu, Hal Daumé III