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135
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DAGM
1998
Springer
15 years 8 months ago
Discrete Mixture Models for Unsupervised Image Segmentation
This paper introduces a novel statistical mixture model for probabilistic clustering of histogram data and, more generally, for the analysis of discrete co occurrence data. Adoptin...
Jan Puzicha, Joachim M. Buhmann, Thomas Hofmann
126
Voted
CHARME
2001
Springer
107views Hardware» more  CHARME 2001»
15 years 7 months ago
Using Combinatorial Optimization Methods for Quantification Scheduling
Model checking is the process of verifying whether a model of a concurrent system satisfies a specified temporal property. Symbolic algorithms based on Binary Decision Diagrams (BD...
Pankaj Chauhan, Edmund M. Clarke, Somesh Jha, Jame...
127
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NIPS
1998
15 years 5 months ago
Learning from Dyadic Data
Dyadic data refers to a domain with two nite sets of objects in which observations are made for dyads, i.e., pairs with one element from either set. This type of data arises natur...
Thomas Hofmann, Jan Puzicha, Michael I. Jordan
121
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CVIU
2007
108views more  CVIU 2007»
15 years 3 months ago
A real-time hand tracker using variable-length Markov models of behaviour
We present a novel approach for visual tracking of structured behaviour as observed in human–computer interaction. An automatically acquired variable-length Markov model is used...
Nikolay Stefanov, Aphrodite Galata, Roger J. Hubbo...
178
Voted
EC
2007
167views ECommerce» more  EC 2007»
15 years 3 months ago
Comparison-Based Algorithms Are Robust and Randomized Algorithms Are Anytime
Randomized search heuristics (e.g., evolutionary algorithms, simulated annealing etc.) are very appealing to practitioners, they are easy to implement and usually provide good per...
Sylvain Gelly, Sylvie Ruette, Olivier Teytaud