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ESANN
2008
15 years 7 months ago
Interpretable ensembles of local models for safety-related applications
Abstract. This paper discusses a machine learning approach for binary classification problems which satisfies the specific requirements of safety-related applications. The approach...
Sebastian Nusser, Clemens Otte, Werner Hauptmann
ICML
1997
IEEE
16 years 7 months ago
Robot Learning From Demonstration
The goal of robot learning from demonstration is to have a robot learn from watching a demonstration of the task to be performed. In our approach to learning from demonstration th...
Christopher G. Atkeson, Stefan Schaal
ICML
2005
IEEE
16 years 7 months ago
Learning as search optimization: approximate large margin methods for structured prediction
Mappings to structured output spaces (strings, trees, partitions, etc.) are typically learned using extensions of classification algorithms to simple graphical structures (eg., li...
Daniel Marcu, Hal Daumé III
IUI
2009
ACM
16 years 3 months ago
Detecting and correcting user activity switches: algorithms and interfaces
The TaskTracer system allows knowledge workers to define a set of activities that characterize their desktop work. It then associates with each user-defined activity the set of ...
Jianqiang Shen, Jed Irvine, Xinlong Bao, Michael G...
NECO
2008
170views more  NECO 2008»
15 years 6 months ago
Representational Power of Restricted Boltzmann Machines and Deep Belief Networks
Deep Belief Networks (DBN) are generative neural network models with many layers of hidden explanatory factors, recently introduced by Hinton et al., along with a greedy layer-wis...
Nicolas Le Roux, Yoshua Bengio