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» Structure learning of Bayesian networks using constraints
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BIBM
2008
IEEE
172views Bioinformatics» more  BIBM 2008»
14 years 1 months ago
Boosting Methods for Protein Fold Recognition: An Empirical Comparison
Protein fold recognition is the prediction of protein’s tertiary structure (Fold) given the protein’s sequence without relying on sequence similarity. Using machine learning t...
Yazhene Krishnaraj, Chandan K. Reddy
AIRS
2006
Springer
13 years 10 months ago
A Novel Ant-Based Clustering Approach for Document Clustering
Recently, much research has been proposed using nature inspired algorithms to perform complex machine learning tasks. Ant Colony Optimization (ACO) is one such algorithm based on s...
Yulan He, Siu Cheung Hui, Yongxiang Sim
CORR
2010
Springer
137views Education» more  CORR 2010»
13 years 6 months ago
Open Graphs and Monoidal Theories
String diagrams are a powerful tool for reasoning about physical processes, logic circuits, tensor networks, and many other compositional structures. The distinguishing feature of...
Lucas Dixon, Aleks Kissinger
C5
2004
IEEE
13 years 10 months ago
Skeleton - Easy Simulation System
Skeleton is a visual scripting environment as an extension of Squeak etoy [1] with Connectors [2] system to make mathematical and physical simulation for non professional computer...
Takashi Yamamiya
ECCV
2010
Springer
13 years 10 months ago
Recursive Coarse-to-Fine Localization for fast Object Detection
Cascading techniques are commonly used to speed-up the scan of an image for object detection. However, cascades of detectors are slow to train due to the high number of detectors a...
Marco Pedersoli, Jordi Gonzàlez, Andrew D. Bagdan...