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» Evaluating algorithms that learn from data streams
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KDD
2012
ACM
201views Data Mining» more  KDD 2012»
13 years 7 months ago
Learning from crowds in the presence of schools of thought
Crowdsourcing has recently become popular among machine learning researchers and social scientists as an effective way to collect large-scale experimental data from distributed w...
Yuandong Tian, Jun Zhu
CIDM
2007
IEEE
15 years 11 months ago
Analysis of streaming GPS measurements of surface displacement through a web services environment
Abstract— We present a method for performing mode classification of real-time streams of GPS surface position data. Our approach has two parts: an algorithm for robust, unconstr...
Robert Granat, Galip Aydin, Marlon E. Pierce, Zhig...
ICDM
2010
IEEE
135views Data Mining» more  ICDM 2010»
15 years 2 months ago
Learning a Bi-Stochastic Data Similarity Matrix
An idealized clustering algorithm seeks to learn a cluster-adjacency matrix such that, if two data points belong to the same cluster, the corresponding entry would be 1; otherwise ...
Fei Wang, Ping Li, Arnd Christian König
ESANN
2003
15 years 6 months ago
Extraction of fuzzy rules from trained neural network using evolutionary algorithm
This paper presents our approach to the rule extraction problem from trained neural network. A method called REX is briefly described. REX acquires a set of fuzzy rules using an ev...
Urszula Markowska-Kaczmar, Wojciech Trelak
164
Voted
PERCOM
2010
ACM
14 years 11 months ago
Detecting activities from body-worn accelerometers via instance-based algorithms
The automatic and unobtrusive identification of user's activities is one of the challenging goals of context-aware computing. This paper discusses and experimentally evaluate...
Nicola Bicocchi, Marco Mamei, Franco Zambonelli