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NN
2007
Springer
162views Neural Networks» more  NN 2007»
14 years 11 months ago
Learning grammatical structure with Echo State Networks
Echo State Networks (ESNs) have been shown to be effective for a number of tasks, including motor control, dynamic time series prediction, and memorizing musical sequences. Howeve...
Matthew H. Tong, Adam D. Bickett, Eric M. Christia...
STOC
2010
ACM
185views Algorithms» more  STOC 2010»
15 years 3 months ago
Measuring independence of datasets
Approximating pairwise, or k-wise, independence with sublinear memory is of considerable importance in the data stream model. In the streaming model the joint distribution is give...
Vladimir Braverman, Rafail Ostrovsky
ICML
2007
IEEE
16 years 19 days ago
Information-theoretic metric learning
In this paper, we present an information-theoretic approach to learning a Mahalanobis distance function. We formulate the problem as that of minimizing the differential relative e...
Jason V. Davis, Brian Kulis, Prateek Jain, Suvrit ...
CVPR
2010
IEEE
15 years 7 months ago
A Novel Riemannian Framework for Shape Analysis of 3D Objects
In this paper we introduce a novel Riemannian framework for shape analysis of parameterized surfaces. We derive a distance function between any two surfaces that is invariant to r...
Sebastian Kurtek, Eric Klassen, Anuj Srivastava, Z...
DEXA
2009
Springer
222views Database» more  DEXA 2009»
15 years 6 months ago
On Index-Free Similarity Search in Metric Spaces
Metric access methods (MAMs) serve as a tool for speeding similarity queries. However, all MAMs developed so far are index-based; they need to build an index on a given database. T...
Tomás Skopal, Benjamin Bustos