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» Algorithmic randomness of continuous functions
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FOCS
1990
IEEE
14 years 22 days ago
Separating Distribution-Free and Mistake-Bound Learning Models over the Boolean Domain
Two of the most commonly used models in computational learning theory are the distribution-free model in which examples are chosen from a fixed but arbitrary distribution, and the ...
Avrim Blum
JMLR
2008
150views more  JMLR 2008»
13 years 8 months ago
Discriminative Learning of Max-Sum Classifiers
The max-sum classifier predicts n-tuple of labels from n-tuple of observable variables by maximizing a sum of quality functions defined over neighbouring pairs of labels and obser...
Vojtech Franc, Bogdan Savchynskyy
SIGECOM
2008
ACM
131views ECommerce» more  SIGECOM 2008»
13 years 8 months ago
Truthful germs are contagious: a local to global characterization of truthfulness
We study the question of how to easily recognize whether a social unction f from an abstract type space to a set of outcomes is truthful, i.e. implementable by a truthful mechanis...
Aaron Archer, Robert Kleinberg
SIAMIS
2011
13 years 3 months ago
NESTA: A Fast and Accurate First-Order Method for Sparse Recovery
Abstract. Accurate signal recovery or image reconstruction from indirect and possibly undersampled data is a topic of considerable interest; for example, the literature in the rece...
Stephen Becker, Jérôme Bobin, Emmanue...
STOC
2010
ACM
211views Algorithms» more  STOC 2010»
14 years 1 months ago
Distributed Computation in Dynamic Networks
In this paper we investigate distributed computation in dynamic networks in which the network topology changes from round to round. We consider a worst-case model in which the com...
Fabian Kuhn, Nancy Lynch and Rotem Oshman