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» Predicting labels for dyadic data
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ICML
2005
IEEE
14 years 10 months ago
High speed obstacle avoidance using monocular vision and reinforcement learning
We consider the task of driving a remote control car at high speeds through unstructured outdoor environments. We present an approach in which supervised learning is first used to...
Jeff Michels, Ashutosh Saxena, Andrew Y. Ng
ICML
2000
IEEE
14 years 10 months ago
FeatureBoost: A Meta-Learning Algorithm that Improves Model Robustness
Most machine learning algorithms are lazy: they extract from the training set the minimum information needed to predict its labels. Unfortunately, this often leads to models that ...
Joseph O'Sullivan, John Langford, Rich Caruana, Av...
VRCAI
2004
ACM
14 years 3 months ago
Determining text readability over textured backgrounds in augmented reality systems
This paper concerns the application of pattern classification techniques to the domain of augmented reality. In many augmented reality applications, one of the ways in which info...
Alex Leykin, Mihran Tuceryan
GECCO
2004
Springer
160views Optimization» more  GECCO 2004»
14 years 3 months ago
Finding Effective Software Metrics to Classify Maintainability Using a Parallel Genetic Algorithm
The ability to predict the quality of a software object can be viewed as a classification problem, where software metrics are the features and expert quality rankings the class lab...
Rodrigo A. Vivanco, Nicolino J. Pizzi
JCDL
2003
ACM
160views Education» more  JCDL 2003»
14 years 3 months ago
Automatic Document Metadata Extraction Using Support Vector Machines
Automatic metadata generation provides scalability and usability for digital libraries and their collections. Machine learning methods offer robust and adaptable automatic metadat...
Hui Han, C. Lee Giles, Eren Manavoglu, Hongyuan Zh...