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NIPS
2003
15 years 8 months ago
Geometric Clustering Using the Information Bottleneck Method
We argue that K–means and deterministic annealing algorithms for geometric clustering can be derived from the more general Information Bottleneck approach. If we cluster the ide...
Susanne Still, William Bialek, Léon Bottou
IJCAI
1989
15 years 8 months ago
Concept Formation by Incremental Conceptual Clustering
Incremental conceptual clustering is an important area of machine learning. It is concerned with summarizing data in a form of concept hierarchies, which will eventually ease the ...
Mirsad Hadzikadic, David Y. Y. Yun
EGPGV
2011
Springer
330views Visualization» more  EGPGV 2011»
14 years 10 months ago
Real-Time Ray Tracer for Visualizing Massive Models on a Cluster
We present a state of the art read-only distributed shared memory (DSM) ray tracer capable of fully utilizing modern cluster hardware to render massive out-of-core polygonal model...
Thiago Ize, Carson Brownlee, Charles D. Hansen
ROMAN
2007
IEEE
127views Robotics» more  ROMAN 2007»
16 years 1 months ago
Incremental on-line hierarchical clustering of whole body motion patterns
Abstract— This paper describes a novel algorithm for autonomous and incremental learning of motion pattern primitives by observation of human motion. Human motion patterns are ed...
Dana Kulic, Wataru Takano, Yoshihiko Nakamura
ICDE
2006
IEEE
164views Database» more  ICDE 2006»
16 years 1 months ago
Clustering Multidimensional Trajectories based on Shape and Velocity
Recently, the analysis of moving objects has become one of the most important technologies to be used in various applications such as GIS, navigation systems, and locationbased in...
Yutaka Yanagisawa, Tetsuji Satoh