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» New Algorithms for Learning in Presence of Errors
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CVPR
2004
IEEE
14 years 10 months ago
Learning a Restricted Bayesian Network for Object Detection
Many classes of images have the characteristics of sparse structuring of statistical dependency and the presence of conditional independencies among various groups of variables. S...
Henry Schneiderman
ML
2000
ACM
154views Machine Learning» more  ML 2000»
13 years 8 months ago
Lazy Learning of Bayesian Rules
The naive Bayesian classifier provides a simple and effective approach to classifier learning, but its attribute independence assumption is often violated in the real world. A numb...
Zijian Zheng, Geoffrey I. Webb
ICML
2006
IEEE
14 years 9 months ago
A statistical approach to rule learning
We present a new, statistical approach to rule learning. Doing so, we address two of the problems inherent in traditional rule learning: The computational hardness of finding rule...
Stefan Kramer, Ulrich Rückert
TSD
2009
Springer
14 years 3 months ago
Intraclausal Coordination and Clause Detection as a Preprocessing Step to Dependency Parsing
Abstract. The impact of clause and intraclausal coordination detection to dependency parsing of Slovene is examined. New methods based on machine learning and heuristic rules are p...
Domen Marincic, Matjaz Gams, Tomaz Sef
RSS
2007
129views Robotics» more  RSS 2007»
13 years 10 months ago
Spatially-Adaptive Learning Rates for Online Incremental SLAM
— Several recent algorithms have formulated the SLAM problem in terms of non-linear pose graph optimization. These algorithms are attractive because they offer lower computationa...
Edwin Olson, John J. Leonard, Seth J. Teller