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» Dynamic Histograms: Capturing Evolving Data Sets
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KDD
2007
ACM
178views Data Mining» more  KDD 2007»
14 years 8 months ago
Density-based clustering for real-time stream data
Existing data-stream clustering algorithms such as CluStream are based on k-means. These clustering algorithms are incompetent to find clusters of arbitrary shapes and cannot hand...
Yixin Chen, Li Tu
ICONIP
2004
13 years 9 months ago
Signature Verification Using Static and Dynamic Features
Abstract. A signature verification algorithm based on static and dynamic features of online signature data is presented. Texture and topological features are the static features of...
Mayank Vatsa, Richa Singh, Pabitra Mitra, Afzel No...
ICTAI
2007
IEEE
14 years 2 months ago
An Adaptive Distributed Ensemble Approach to Mine Concept-Drifting Data Streams
An adaptive boosting ensemble algorithm for classifying homogeneous distributed data streams is presented. The method builds an ensemble of classifiers by using Genetic Programmi...
Gianluigi Folino, Clara Pizzuti, Giandomenico Spez...
CVPR
2010
IEEE
14 years 4 months ago
Moving Vistas: Exploiting Motion for Describing Scenes
Scene recognition in an unconstrained setting is an open and challenging problem with wide applications. In this paper, we study the role of scene dynamics for improved representa...
Nitesh Shroff, Pavan Turaga, Rama Chellappa
ICDE
2006
IEEE
201views Database» more  ICDE 2006»
14 years 9 months ago
Counting at Large: Efficient Cardinality Estimation in Internet-Scale Data Networks
Counting in general, and estimating the cardinality of (multi-) sets in particular, is highly desirable for a large variety of applications, representing a foundational block for ...
Nikos Ntarmos, Peter Triantafillou, Gerhard Weikum