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» Maximum likelihood analysis of algorithms and data structure...
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144
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ICML
2005
IEEE
16 years 4 months ago
Supervised dimensionality reduction using mixture models
Given a classification problem, our goal is to find a low-dimensional linear transformation of the feature vectors which retains information needed to predict the class labels. We...
Sajama, Alon Orlitsky
124
Voted
NIPS
2007
15 years 5 months ago
Expectation Maximization and Posterior Constraints
The expectation maximization (EM) algorithm is a widely used maximum likelihood estimation procedure for statistical models when the values of some of the variables in the model a...
João Graça, Kuzman Ganchev, Ben Task...
WOB
2003
140views Bioinformatics» more  WOB 2003»
15 years 5 months ago
Computing Maximum Subsequence in Parallel
The maximum subsequence problem finds the contiguous subsequence of n real numbers with the highest sum. This is an important problem that arises in several contexts in Computatio...
Carlos E. R. Alves, Edson Cáceres, Siang W....
ICIP
2003
IEEE
16 years 5 months ago
EM-based simultaneous registration, restoration, and interpolation of super-resolved images
We present a maximum likelihood (Ml) solution to the problem of obtaining high-resolution images from sequences of noisy, blurred, and low-resolution images. In our formulation, t...
Nathan A. Woods, Nikolas P. Galatsanos, Aggelos K....
127
Voted
INFOCOM
2007
IEEE
15 years 10 months ago
Distributed Low-Complexity Maximum-Throughput Scheduling for Wireless Backhaul Networks
— We introduce a low-complexity distributed slotted MAC protocol that can support all feasible arrival rates in a wireless backhaul network (WBN). For arbitrary wireless networks...
Abdul Kader Kabbani, Theodoros Salonidis, Edward W...