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PAKDD
2004
ACM
137views Data Mining» more  PAKDD 2004»
14 years 4 months ago
Fast and Light Boosting for Adaptive Mining of Data Streams
Supporting continuous mining queries on data streams requires algorithms that (i) are fast, (ii) make light demands on memory resources, and (iii) are easily to adapt to concept dr...
Fang Chu, Carlo Zaniolo
EUROGP
2010
Springer
166views Optimization» more  EUROGP 2010»
14 years 4 months ago
Learning a Lot from Only a Little: Genetic Programming for Panel Segmentation on Sparse Sensory Evaluation Data
We describe a data mining framework that derives panelist information from sparse flavour survey data. One component of the framework executes genetic programming ensemble based s...
Katya Vladislavleva, Kalyan Veeramachaneni, Una-Ma...
IJCAI
2007
14 years 11 days ago
Ensembles of Partially Trained SVMs with Multiplicative Updates
The training of support vector machines (SVM) involves a quadratic programming problem, which is often optimized by a complicated numerical solver. In this paper, we propose a muc...
Ivor W. Tsang, James T. Kwok
ICPR
2008
IEEE
14 years 5 months ago
Adaptive context recognition based on audio signal
Auditory data provide many contextual cues about the crucial content of environments around. The goal of audio based context recognition is to equip the sensing devices with class...
Zhi Zeng, Xin Li, Xiaohong Ma, Qiang Ji
KDD
2002
ACM
157views Data Mining» more  KDD 2002»
14 years 11 months ago
Exploiting unlabeled data in ensemble methods
An adaptive semi-supervised ensemble method, ASSEMBLE, is proposed that constructs classification ensembles based on both labeled and unlabeled data. ASSEMBLE alternates between a...
Kristin P. Bennett, Ayhan Demiriz, Richard Maclin