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» How to process uncertainty in machine learning
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GECCO
2005
Springer
152views Optimization» more  GECCO 2005»
14 years 2 months ago
GAMM: genetic algorithms with meta-models for vision
Recent adaptive image interpretation systems can reach optimal performance for a given domain via machine learning, without human intervention. The policies are learned over an ex...
Greg Lee, Vadim Bulitko
RAS
2010
109views more  RAS 2010»
13 years 7 months ago
Combining active learning and reactive control for robot grasping
Grasping an object is a task that inherently needs to be treated in a hybrid fashion. The system must decide both where and how to grasp the object. While selecting where to grasp...
Oliver Krömer, Renaud Detry, Justus H. Piater...
IR
2011
13 years 3 months ago
Learning to rank for why-question answering
In this paper, we evaluate a number of machine learning techniques for the task of ranking answers to why-questions. We use TF-IDF together with a set of 36 linguistically motivate...
Suzan Verberne, Hans van Halteren, Daphne Theijsse...
ICALT
2008
IEEE
14 years 3 months ago
Students' Tracking Data: An Approach for Efficiently Tracking Computer Mediated Communications in Distance Learning
This paper presents an approach for closely observing the different levels of Human and Computer Interactions during student’s communication activities on Computer Mediated Comm...
Madeth May, Sébastien George, Patrick Pr&ea...
ICALT
2006
IEEE
14 years 2 months ago
ANNANN - Next Steps for Scaffolding Learning About Programs
It is difficult for a student to learn how to program and to build an understanding of the rationale which underpins the development of a program’s componentparts. Conventional ...
Su White, Clare J. Hooper, Leslie Carr, Timothy P....