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» A Spectral Approach to Lower Bounds
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ICML
2002
IEEE
14 years 8 months ago
On generalization bounds, projection profile, and margin distribution
We study generalization properties of linear learning algorithms and develop a data dependent approach that is used to derive generalization bounds that depend on the margin distr...
Ashutosh Garg, Sariel Har-Peled, Dan Roth
SIAMDM
2008
79views more  SIAMDM 2008»
13 years 7 months ago
Testing Triangle-Freeness in General Graphs
In this paper we consider the problem of testing whether a graph is triangle-free, and more generally, whether it is H-free, for a fixed subgraph H. The algorithm should accept gr...
Noga Alon, Tali Kaufman, Michael Krivelevich, Dana...
SIAMCO
2010
114views more  SIAMCO 2010»
13 years 2 months ago
Discrete Carleman Estimates for Elliptic Operators in Arbitrary Dimension and Applications
In arbitrary dimension, we consider the semi-discrete elliptic operator -2 t + AM , where AM is a finite difference approximation of the operator - x((x) x). For this operator we d...
Franck Boyer, Florence Hubert, Jérôme...
ICDM
2008
IEEE
122views Data Mining» more  ICDM 2008»
14 years 1 months ago
Nonnegative Matrix Factorization for Combinatorial Optimization: Spectral Clustering, Graph Matching, and Clique Finding
Nonnegative matrix factorization (NMF) is a versatile model for data clustering. In this paper, we propose several NMF inspired algorithms to solve different data mining problems....
Chris H. Q. Ding, Tao Li, Michael I. Jordan
MFCS
2007
Springer
14 years 1 months ago
Uncover Low Degree Vertices and Minimise the Mess: Independent Sets in Random Regular Graphs
Abstract. We present algorithmic lower bounds on the size of the largest independent sets of vertices in a random d-regular graph. Our bounds hold with probability approaching one ...
William Duckworth, Michele Zito