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ICML
2005
IEEE
16 years 5 months ago
Analysis and extension of spectral methods for nonlinear dimensionality reduction
Many unsupervised algorithms for nonlinear dimensionality reduction, such as locally linear embedding (LLE) and Laplacian eigenmaps, are derived from the spectral decompositions o...
Fei Sha, Lawrence K. Saul
MLDM
2005
Springer
15 years 10 months ago
Linear Manifold Clustering
In this paper we describe a new cluster model which is based on the concept of linear manifolds. The method identifies subsets of the data which are embedded in arbitrary oriented...
Robert M. Haralick, Rave Harpaz
149
Voted
COLT
2004
Springer
15 years 8 months ago
Regret Bounds for Hierarchical Classification with Linear-Threshold Functions
We study the problem of classifying data in a given taxonomy when classifications associated with multiple and/or partial paths are allowed. We introduce an incremental algorithm u...
Nicolò Cesa-Bianchi, Alex Conconi, Claudio ...
142
Voted
ECTEL
2010
Springer
15 years 5 months ago
Components of a Research 2.0 Infrastructure
In this paper, we investigate the components of a Research 2.0 infrastructure. We propose building blocks and their concrete implementation to leverage Research 2.0 practice and te...
Thomas Daniel Ullmann, Fridolin Wild, Peter Scott,...
162
Voted
UAI
1996
15 years 6 months ago
Bayesian Learning of Loglinear Models for Neural Connectivity
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...
Kathryn B. Laskey, Laura Martignon