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IDA
2001
Springer
15 years 11 months ago
An Algorithm for Segmenting Categorical Time Series into Meaningful Episodes
This paper describes an unsupervised algorithm for segmenting categorical time series. The algorithm first collects statistics about the frequency and boundary entropy of ngrams, t...
Paul R. Cohen, Niall M. Adams
CORR
2010
Springer
103views Education» more  CORR 2010»
15 years 7 months ago
Exploratory Analysis of Functional Data via Clustering and Optimal Segmentation
We propose in this paper an exploratory analysis algorithm for functional data. The method partitions a set of functions into K clusters and represents each cluster by a simple pr...
Georges Hébrail, Bernard Hugueney, Yves Lec...
IPL
2002
107views more  IPL 2002»
15 years 6 months ago
Binary space partitions for axis-parallel line segments: Size-height tradeoffs
We present worst-case lower bounds on the minimum size of a binary space partition (BSP) tree as a function of its height, for a set S of n axis-parallel line segments in the plan...
Sunil Arya
ICRA
2010
IEEE
190views Robotics» more  ICRA 2010»
15 years 5 months ago
Active 3D scene segmentation and detection of unknown objects
Abstract— We present an active vision system for segmentation of visual scenes based on integration of several cues. The system serves as a visual front end for generation of obj...
Mårten Björkman, Danica Kragic
ICML
2000
IEEE
16 years 7 months ago
Maximum Entropy Markov Models for Information Extraction and Segmentation
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...
Andrew McCallum, Dayne Freitag, Fernando C. N. Per...