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NECO
2010
136views more  NECO 2010»
13 years 7 months ago
Learning to Represent Spatial Transformations with Factored Higher-Order Boltzmann Machines
To allow the hidden units of a restricted Boltzmann machine to model the transformation between two successive images, Memisevic and Hinton (2007) introduced three-way multiplicat...
Roland Memisevic, Geoffrey E. Hinton
CCIA
2010
Springer
13 years 4 months ago
Learning Force-Based Robot Skills from Haptic Demonstration
Locally weighted as well as Gaussian mixtures learning algorithms are suitable strategies for trajectory learning and skill acquisition, in the context of programming by demonstrat...
Leonel Rozo, Pablo Jiménez, Carme Torras
CVPR
2006
IEEE
14 years 11 months ago
Meta-Evaluation of Image Segmentation Using Machine Learning
Image segmentation is a fundamental step in many computer vision applications. Generally, the choice of a segmentation algorithm, or parameterization of a given algorithm, is sele...
Hui Zhang, Sharath R. Cholleti, Sally A. Goldman, ...
ICML
2000
IEEE
14 years 10 months ago
Correlation-based Feature Selection for Discrete and Numeric Class Machine Learning
Algorithms for feature selection fall into two broad categories: wrappers that use the learning algorithm itself to evaluate the usefulness of features and filters that evaluate f...
Mark A. Hall
SEKE
2007
Springer
14 years 3 months ago
Adjudicator: A Statistical Approach for Learning Ontology Concepts from Peer Agents
— We present a statistical approach for software agents to learn ontology concepts from peer agents by asking them whether they can reach consensus on significant differences bet...
Behrouz Homayoun Far, Abdel Halim Elamy, Nora Houa...