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CORR
2010
Springer
70views Education» more  CORR 2010»
15 years 6 months ago
Structured sparsity-inducing norms through submodular functions
Sparse methods for supervised learning aim at finding good linear predictors from as few variables as possible, i.e., with small cardinality of their supports. This combinatorial ...
Francis Bach
AUTOMATICA
2004
113views more  AUTOMATICA 2004»
15 years 6 months ago
Ellipsoidal bounds for uncertain linear equations and dynamical systems
In this paper, we discuss semidefinite relaxation techniques for computing minimal size ellipsoids that bound the solution set of a system of uncertain linear equations. The propo...
Giuseppe Carlo Calafiore, Laurent El Ghaoui
TCSV
2002
114views more  TCSV 2002»
15 years 6 months ago
Multicast and unicast real-time video streaming over wireless LANs
In this paper, we address the problem of real-time video streaming over wireless LANs for both unicast and multicast transmission. The wireless channel is modeled as a packet-erasu...
Abhik Majumdar, Daniel Grobe Sachs, Igor Kozintsev...
DEXAW
2009
IEEE
173views Database» more  DEXAW 2009»
16 years 1 months ago
Automatic Cluster Number Selection Using a Split and Merge K-Means Approach
Abstract—The k-means method is a simple and fast clustering technique that exhibits the problem of specifying the optimal number of clusters preliminarily. We address the problem...
Markus Muhr, Michael Granitzer

Book
357views
17 years 4 months ago
Foundations of Constraint Satisfaction
"Constraint satisfaction is a general problem in which the goal is to find values for a set of variables that will satisfy a given set of constraints. It is the core of many a...
Edward Tsang