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» Intrinsic Geometries in Learning
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210
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AR
2011
14 years 8 months ago
Learning, Generation and Recognition of Motions by Reference-Point-Dependent Probabilistic Models
This paper presents a novel method for learning object manipulation such as rotating an object or placing one object on another. In this method, motions are learned using referenc...
Komei Sugiura, Naoto Iwahashi, Hideki Kashioka, Sa...
108
Voted
AIED
2007
Springer
15 years 5 months ago
Is Over Practice Necessary? - Improving Learning Efficiency with the Cognitive Tutor through Educational Data Mining
This study examined the effectiveness of an educational data mining method
Hao Cen, Kenneth R. Koedinger, Brian Junker
99
Voted
NIPS
2007
15 years 3 months ago
Learning the structure of manifolds using random projections
We present a simple variant of the k-d tree which automatically adapts to intrinsic low dimensional structure in data.
Yoav Freund, Sanjoy Dasgupta, Mayank Kabra, Nakul ...
FGR
2004
IEEE
238views Biometrics» more  FGR 2004»
15 years 5 months ago
Nearest Manifold Approach for Face Recognition
Faces under varying illumination, pose and non-rigid deformation are empirically thought of as a highly nonlinear manifold in the observation space. How to discover intrinsic low-...
Junping Zhang, Stan Z. Li, Jue Wang
AAAI
2008
15 years 4 months ago
A Case Study on the Critical Role of Geometric Regularity in Machine Learning
An important feature of many problem domains in machine learning is their geometry. For example, adjacency relationships, symmetries, and Cartesian coordinates are essential to an...
Jason Gauci, Kenneth O. Stanley