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KDD
2008
ACM
172views Data Mining» more  KDD 2008»
16 years 7 months ago
Structured metric learning for high dimensional problems
The success of popular algorithms such as k-means clustering or nearest neighbor searches depend on the assumption that the underlying distance functions reflect domain-specific n...
Jason V. Davis, Inderjit S. Dhillon
PODS
2007
ACM
225views Database» more  PODS 2007»
16 years 6 months ago
Sketching unaggregated data streams for subpopulation-size queries
IP packet streams consist of multiple interleaving IP flows. Statistical summaries of these streams, collected for different measurement periods, are used for characterization of ...
Edith Cohen, Nick G. Duffield, Haim Kaplan, Carste...
SAC
2005
ACM
16 years 4 days ago
Estimating manifold dimension by inversion error
Video and image datasets can often be described by a small number of parameters, even though each image usually consists of hundreds or thousands of pixels. This observation is of...
Shawn Martin, Alex Bäcker
SBIA
2004
Springer
15 years 12 months ago
Learning with Drift Detection
Abstract. Most of the work in machine learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem...
João Gama, Pedro Medas, Gladys Castillo, Pe...
WSC
1998
15 years 8 months ago
Emulation of a Material Delivery System
Emulation is the process of exactly imitating a real system. Recent advances in simulation technology make it possible to emulate real world control systems by using a system'...
Todd LeBaron, Kelly Thompson