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» Reductions among high dimensional proximity problems
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KDD
2006
ACM
213views Data Mining» more  KDD 2006»
14 years 8 months ago
Learning sparse metrics via linear programming
Calculation of object similarity, for example through a distance function, is a common part of data mining and machine learning algorithms. This calculation is crucial for efficie...
Glenn Fung, Rómer Rosales
SBRN
2008
IEEE
14 years 1 months ago
Imitation Learning of an Intelligent Navigation System for Mobile Robots Using Reservoir Computing
The design of an autonomous navigation system for mobile robots can be a tough task. Noisy sensors, unstructured environments and unpredictability are among the problems which mus...
Eric A. Antonelo, Benjamin Schrauwen, Dirk Strooba...
HICSS
2005
IEEE
91views Biometrics» more  HICSS 2005»
14 years 1 months ago
Size Does Matter in Computer Collaboration: Heterogeneous Platform Effects on Human-Human Interaction
Because today’s workforce is highly mobile, small wireless devices are being used to support mobile work collaboration. However, do computer platform differences affect such col...
Marilyn Tremaine, Aleksandra Sarcevic, Dezhi Wu, M...
CSDA
2008
108views more  CSDA 2008»
13 years 7 months ago
The random Tukey depth
The computation of the Tukey depth, also called halfspace depth, is very demanding, even in low dimensional spaces, because it requires that all possible one-dimensional projectio...
J. A. Cuesta-Albertos, A. Nieto-Reyes
JCIT
2010
190views more  JCIT 2010»
13 years 2 months ago
Application of Feature Extraction Method in Customer Churn Prediction Based on Random Forest and Transduction
With the development of telecom business, customer churn prediction becomes more and more important. An outstanding issue in customer churn prediction is high dimensional problem....
Yihui Qiu, Hong Li