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VL
2010
IEEE
216views Visual Languages» more  VL 2010»
15 years 4 months ago
Explanatory Debugging: Supporting End-User Debugging of Machine-Learned Programs
Many machine-learning algorithms learn rules of behavior from individual end users, such as taskoriented desktop organizers and handwriting recognizers. These rules form a “prog...
Todd Kulesza, Simone Stumpf, Margaret M. Burnett, ...
MICCAI
2007
Springer
16 years 7 months ago
Active-Contour-Based Image Segmentation Using Machine Learning Techniques
Abstract. We introduce a non-linear shape prior for the deformable model framework that we learn from a set of shape samples using recent manifold learning techniques. We model a c...
Patrick Etyngier, Florent Ségonne, Renaud K...
ICARIS
2009
Springer
16 years 1 months ago
On AIRS and Clonal Selection for Machine Learning
AIRS is an immune-inspired supervised learning algorithm that has been shown to perform competitively on some common datasets. Previous analysis of the algorithm consists almost ex...
Chris McEwan, Emma Hart
KI
2009
Springer
16 years 1 months ago
Machine Learning Techniques for Selforganizing Combustion Control
Abstract. This paper presents the overall system of a learning, selforganizing, and adaptive controller used to optimize the combustion process in a hard-coal fired power plant. T...
Erik Schaffernicht, Volker Stephan, Klaus Debes, H...
VL
2010
IEEE
160views Visual Languages» more  VL 2010»
15 years 4 months ago
Toward End-User Debugging of Machine-Learned Classifiers
Many machine-learning algorithms learn rules of behavior from individual end users, such as taskoriented desktop organizers and handwriting recognizers. These rules form a generat...
Todd Kulesza