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» A randomized embedding algorithm for trees
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DATE
2009
IEEE
113views Hardware» more  DATE 2009»
14 years 3 months ago
Incorporating graceful degradation into embedded system design
In this work, the focus is put on the behavior of a system in case a fault occurs that disables the system from executing its applications. Instead of executing a random subset of...
Michael Glaß, Martin Lukasiewycz, Christian ...
COLING
2008
13 years 10 months ago
Unsupervised Induction of Labeled Parse Trees by Clustering with Syntactic Features
We present an algorithm for unsupervised induction of labeled parse trees. The algorithm has three stages: bracketing, initial labeling, and label clustering. Bracketing is done f...
Roi Reichart, Ari Rappoport
ICASSP
2008
IEEE
14 years 3 months ago
Wavelet-domain compressive signal reconstruction using a Hidden Markov Tree model
Compressive sensing aims to recover a sparse or compressible signal from a small set of projections onto random vectors; conventional solutions involve linear programming or greed...
Marco F. Duarte, Michael B. Wakin, Richard G. Bara...
SIBGRAPI
1999
IEEE
14 years 1 months ago
Deterministic Texture Analysis and Synthesis Using Tree Structure Vector Quantization
Texture analysis and synthesis is very important for computer graphics, vision, and image processing. This paper describes an algorithm which can produce new textures with a matchi...
Li-Yi Wei
PAMI
2007
166views more  PAMI 2007»
13 years 8 months ago
A Comparison of Decision Tree Ensemble Creation Techniques
Abstract—We experimentally evaluate bagging and seven other randomizationbased approaches to creating an ensemble of decision tree classifiers. Statistical tests were performed o...
Robert E. Banfield, Lawrence O. Hall, Kevin W. Bow...