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IWANN
2009
Springer
14 years 3 months ago
Optimising Machine-Learning-Based Fault Prediction in Foundry Production
Abstract. Microshrinkages are known as probably the most difficult defects to avoid in high-precision foundry. The presence of this failure renders the casting invalid, with the su...
Igor Santos, Javier Nieves, Yoseba K. Penya, Pablo...
CORR
2010
Springer
128views Education» more  CORR 2010»
13 years 8 months ago
Sublinear Optimization for Machine Learning
Abstract--We give sublinear-time approximation algorithms for some optimization problems arising in machine learning, such as training linear classifiers and finding minimum enclos...
Kenneth L. Clarkson, Elad Hazan, David P. Woodruff
FUIN
2002
80views more  FUIN 2002»
13 years 8 months ago
P Systems with Replicated Rewriting and Stream X-Machines (Eilenberg Machines)
Abstract. The aim of this paper is to show how the P systems with replicated rewriting can be modeled by X-machines (also called Eilenberg machines). In the first approach, the par...
Joaquin Aguado, Tudor Balanescu, Anthony J. Cowlin...
CVPR
2004
IEEE
14 years 10 months ago
Learning Classifiers from Imbalanced Data Based on Biased Minimax Probability Machine
We consider the problem of the binary classification on imbalanced data, in which nearly all the instances are labelled as one class, while far fewer instances are labelled as the...
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. ...
ICML
2010
IEEE
13 years 6 months ago
Approximate Predictive Representations of Partially Observable Systems
We provide a novel view of learning an approximate model of a partially observable environment from data and present a simple implemenf the idea. The learned model abstracts away ...
Monica Dinculescu, Doina Precup