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» Evaluating algorithms that learn from data streams
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98
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ECML
2006
Springer
15 years 2 months ago
Cascade Evaluation of Clustering Algorithms
Abstract. This paper is about the evaluation of the results of clustering algorithms, and the comparison of such algorithms. We propose a new method based on the enrichment of a se...
Laurent Candillier, Isabelle Tellier, Fabien Torre...
AI
2002
Springer
15 years 14 days ago
Learning Bayesian networks from data: An information-theory based approach
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
121
Voted
GECCO
2009
Springer
204views Optimization» more  GECCO 2009»
15 years 5 months ago
Combined structure and motion extraction from visual data using evolutionary active learning
We present a novel stereo vision modeling framework that generates approximate, yet physically-plausible representations of objects rather than creating accurate models that are c...
Krishnanand N. Kaipa, Josh C. Bongard, Andrew N. M...
120
Voted
MICCAI
2007
Springer
15 years 6 months ago
Robust Autonomous Model Learning from 2D and 3D Data Sets
In this paper we propose a weakly supervised learning algorithm for appearance models based on the minimum description length (MDL) principle. From a set of training images or volu...
Georg Langs, Rene Donner, Philipp Peloschek, Horst...
100
Voted
VLDB
2004
ACM
203views Database» more  VLDB 2004»
15 years 6 months ago
PLACE: A Query Processor for Handling Real-time Spatio-temporal Data Streams
The emergence of location-aware services calls for new real-time spatio-temporal query processing algorithms that deal with large numbers of mobile objects and queries. In this de...
Mohamed F. Mokbel, Xiaopeng Xiong, Walid G. Aref, ...