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» Kernel methods and the exponential family
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JMLR
2006
186views more  JMLR 2006»
13 years 7 months ago
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples
We propose a family of learning algorithms based on a new form of regularization that allows us to exploit the geometry of the marginal distribution. We focus on a semi-supervised...
Mikhail Belkin, Partha Niyogi, Vikas Sindhwani
TIP
2010
136views more  TIP 2010»
13 years 5 months ago
Wavelet Steerability and the Higher-Order Riesz Transform
Abstract— Our main goal in this paper is to set the foundations of a general continuous-domain framework for designing steerable, reversible signal transformations (a.k.a. frames...
Michael Unser, Dimitri Van De Ville
COLT
2010
Springer
13 years 5 months ago
Forest Density Estimation
We study graph estimation and density estimation in high dimensions, using a family of density estimators based on forest structured undirected graphical models. For density estim...
Anupam Gupta, John D. Lafferty, Han Liu, Larry A. ...
RECOMB
2004
Springer
14 years 7 months ago
The evolutionary capacity of protein structures
In nature, one finds large collections of different protein sequences exhibiting roughly the same three-dimensional structure, and this observation underpins the study of structur...
Leonid Meyerguz, David Kempe, Jon M. Kleinberg, Ro...
ICCV
2011
IEEE
12 years 7 months ago
The Power of Comparative Reasoning
Rank correlation measures are known for their resilience to perturbations in numeric values and are widely used in many evaluation metrics. Such ordinal measures have rarely been ...
Jay Yagnik, Dennis Strelow, David Ross, Ruei-sung ...