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ETVC
2008
13 years 9 months ago
Intrinsic Geometries in Learning
In a seminal paper, Amari (1998) proved that learning can be made more efficient when one uses the intrinsic Riemannian structure of the algorithms' spaces of parameters to po...
Richard Nock, Frank Nielsen
IJCAI
2007
13 years 9 months ago
Learning from Partial Observations
We present a general machine learning framework for modelling the phenomenon of missing information in data. We propose a masking process model to capture the stochastic nature of...
Loizos Michael
PAMI
2007
118views more  PAMI 2007»
13 years 7 months ago
Learning to Transform Time Series with a Few Examples
We describe a semi-supervised regression algorithm that learns to transform one time series into another time series given examples of the transformation. This algorithm is applie...
Ali Rahimi, Ben Recht, Trevor Darrell
ICML
2007
IEEE
14 years 8 months ago
Spectral feature selection for supervised and unsupervised learning
Feature selection aims to reduce dimensionality for building comprehensible learning models with good generalization performance. Feature selection algorithms are largely studied ...
Zheng Zhao, Huan Liu
ECAL
2005
Springer
14 years 1 months ago
A Dynamical Systems Approach to Learning: A Frequency-Adaptive Hopper Robot
We present an example of the dynamical systems approach to learning and adaptation. Our goal is to explore how both control and learning can be embedded into a single dynamical sys...
Jonas Buchli, Ludovic Righetti, Auke Jan Ijspeert