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ML
1998
ACM
139views Machine Learning» more  ML 1998»
15 years 2 months ago
The Hierarchical Hidden Markov Model: Analysis and Applications
We introduce, analyze and demonstrate a recursive hierarchical generalization of the widely used hidden Markov models, which we name Hierarchical Hidden Markov Models (HHMM). Our m...
Shai Fine, Yoram Singer, Naftali Tishby
COLT
2008
Springer
15 years 5 months ago
Model Selection and Stability in k-means Clustering
Clustering Stability methods are a family of widely used model selection techniques applied in data clustering. Their unifying theme is that an appropriate model should result in ...
Ohad Shamir, Naftali Tishby
IJAR
2007
87views more  IJAR 2007»
15 years 3 months ago
Pruning belief decision tree methods in averaging and conjunctive approaches
The belief decision tree (BDT) approach is a decision tree in an uncertain environment where the uncertainty is represented through the Transferable Belief Model (TBM), one interp...
Salsabil Trabelsi, Zied Elouedi, Khaled Mellouli
CVPR
2012
IEEE
13 years 5 months ago
Semantic segmentation using regions and parts
We address the problem of segmenting and recognizing objects in real world images, focusing on challenging articulated categories such as humans and other animals. For this purpos...
Pablo Arbelaez, Bharath Hariharan, Chunhui Gu, Sau...
ICRA
2005
IEEE
116views Robotics» more  ICRA 2005»
15 years 8 months ago
Using Hierarchical EM to Extract Planes from 3D Range Scans
— Recently, the acquisition of three-dimensional maps has become more and more popular. This is motivated by the fact that robots act in the three-dimensional world and several t...
Rudolph Triebel, Wolfram Burgard, Frank Dellaert