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STOC
2004
ACM
150views Algorithms» more  STOC 2004»
16 years 7 months ago
Typical properties of winners and losers in discrete optimization
We present a probabilistic analysis for a large class of combinatorial optimization problems containing, e.g., all binary optimization problems defined by linear constraints and a...
René Beier, Berthold Vöcking
CGO
2004
IEEE
15 years 10 months ago
VHC: Quickly Building an Optimizer for Complex Embedded Architectures
To meet the high demand for powerful embedded processors, VLIW architectures are increasingly complex (e.g., multiple clusters), and moreover, they now run increasingly sophistica...
Michael Dupré, Nathalie Drach, Olivier Tema...
ICALP
2009
Springer
16 years 7 months ago
Correlation Clustering Revisited: The "True" Cost of Error Minimization Problems
Correlation Clustering was defined by Bansal, Blum, and Chawla as the problem of clustering a set of elements based on a possibly inconsistent binary similarity function between e...
Nir Ailon, Edo Liberty
INFOCOM
2009
IEEE
16 years 1 months ago
Distributed Opportunistic Scheduling With Two-Level Channel Probing
Distributed opportunistic scheduling (DOS) is studied for wireless ad-hoc networks in which many links contend for the channel using random access before data transmissions. Simpl...
P. S. Chandrashekhar Thejaswi, Junshan Zhang, Man-...
NECO
2011
15 years 1 months ago
Least Squares Estimation Without Priors or Supervision
Selection of an optimal estimator typically relies on either supervised training samples (pairs of measurements and their associated true values), or a prior probability model for...
Martin Raphan, Eero P. Simoncelli