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CORR
2008
Springer
118views Education» more  CORR 2008»
15 years 6 months ago
Learning Low-Density Separators
Abstract. We define a novel, basic, unsupervised learning problem learning the the lowest density homogeneous hyperplane separator of an unknown probability distribution. This task...
Shai Ben-David, Tyler Lu, Dávid Pál,...
CORR
2008
Springer
158views Education» more  CORR 2008»
15 years 6 months ago
Improved Smoothed Analysis of the k-Means Method
The k-means method is a widely used clustering algorithm. One of its distinguished features is its speed in practice. Its worst-case running-time, however, is exponential, leaving...
Bodo Manthey, Heiko Röglin
CORR
2006
Springer
102views Education» more  CORR 2006»
15 years 6 months ago
Structural Inference of Hierarchies in Networks
One property of networks that has received comparatively little attention is hierarchy, i.e., the property of having vertices that cluster together in groups, which then join to f...
Aaron Clauset, Cristopher Moore, M. E. J. Newman
CORR
2006
Springer
99views Education» more  CORR 2006»
15 years 6 months ago
PAC Learning Mixtures of Axis-Aligned Gaussians with No Separation Assumption
Abstract. We propose and analyze a new vantage point for the learning of mixtures of Gaussians: namely, the PAC-style model of learning probability distributions introduced by Kear...
Jon Feldman, Ryan O'Donnell, Rocco A. Servedio
ENDM
2006
77views more  ENDM 2006»
15 years 6 months ago
A Two-stage Model for a Day-ahead Paratransit Planning Problem
We consider a dynamic planning problem for paratransit transportation. The focus is on a decision to take one day ahead: which requests to serve with own vehicles, and which reque...
Maria L. A. G. Cremers, Willem K. Klein Haneveld, ...