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» Algorithmic randomness of continuous functions
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FOCS
1990
IEEE
15 years 10 months 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»
15 years 6 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»
15 years 6 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
15 years 29 days 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»
15 years 11 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