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» Evaluating algorithms that learn from data streams
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DCC
2006
IEEE
16 years 6 months ago
Fast Lossless Compression of Scientific Floating-Point Data
In scientific computing environments, large amounts of floating-point data often need to be transferred between computers as well as to and from storage devices. Compression can r...
Paruj Ratanaworabhan, Jian Ke, Martin Burtscher
DAGM
2010
Springer
15 years 8 months ago
On-Line Multi-view Forests for Tracking
Abstract. A successful approach to tracking is to on-line learn discriminative classifiers for the target objects. Although these trackingby-detection approaches are usually fast a...
Christian Leistner, Martin Godec, Amir Saffari, Ho...
ICDM
2007
IEEE
132views Data Mining» more  ICDM 2007»
16 years 1 months ago
Learning What Makes a Society Tick
We present a machine learning methodology (models, algorithms, and experimental data) to discovering the agent dynamics that drive the evolution of the social groups in a communit...
Hung-Ching Chen, Mark K. Goldberg, Malik Magdon-Is...
CVPR
2007
IEEE
16 years 8 months ago
A Bio-inspired Learning Approach for the Classification of Risk Zones in a Smart Space
Learning from experience is a basic task of human brain that is not yet fulfilled satisfactorily by computers. Therefore, in recent years to cope with this issue, bio-inspired app...
Alessio Dore, Matteo Pinasco, Carlo S. Regazzoni
ALT
2006
Springer
16 years 3 months ago
Probabilistic Generalization of Simple Grammars and Its Application to Reinforcement Learning
Abstract. Recently, some non-regular subclasses of context-free grammars have been found to be efficiently learnable from positive data. In order to use these efficient algorithms ...
Takeshi Shibata, Ryo Yoshinaka, Takashi Chikayama