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ECAI
2008
Springer
14 years 1 months ago
An Ensemble of Classifiers for coping with Recurring Contexts in Data Streams
Abstract. This paper proposes a general framework for classifying data streams by exploiting incremental clustering in order to dynamically build and update an ensemble of incremen...
Ioannis Katakis, Grigorios Tsoumakas, Ioannis P. V...
ICDM
2003
IEEE
95views Data Mining» more  ICDM 2003»
14 years 4 months ago
Evolutionary Gabor Filter Optimization with Application to Vehicle Detection
Abstract—Despite the considerable amount of research work on the application of Gabor filters in pattern classification, their design and selection have been mostly done on a t...
Zehang Sun, George Bebis, Ronald Miller
KDD
2007
ACM
152views Data Mining» more  KDD 2007»
14 years 12 months ago
Efficient incremental constrained clustering
Clustering with constraints is an emerging area of data mining research. However, most work assumes that the constraints are given as one large batch. In this paper we explore the...
Ian Davidson, S. S. Ravi, Martin Ester
ICCV
2007
IEEE
15 years 1 months ago
Mode-seeking by Medoidshifts
We present a nonparametric mode-seeking algorithm, called medoidshift, based on approximating the local gradient using a weighted estimate of medoids. Like meanshift, medoidshift ...
Yaser Sheikh, Erum A. Khan, Takeo Kanade
CVPR
2008
IEEE
15 years 1 months ago
Incremental learning of nonparametric Bayesian mixture models
Clustering is a fundamental task in many vision applications. To date, most clustering algorithms work in a batch setting and training examples must be gathered in a large group b...
Ryan Gomes, Max Welling, Pietro Perona