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» Polynomial Learning of Distribution Families
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COMPGEOM
2011
ACM
13 years 1 months ago
Comparing distributions and shapes using the kernel distance
Starting with a similarity function between objects, it is possible to define a distance metric (the kernel distance) on pairs of objects, and more generally on probability distr...
Sarang C. Joshi, Raj Varma Kommaraju, Jeff M. Phil...
IDA
2005
Springer
14 years 3 months ago
Combining Bayesian Networks with Higher-Order Data Representations
Abstract. This paper introduces Higher-Order Bayesian Networks, a probabilistic reasoning formalism which combines the efficient reasoning mechanisms of Bayesian Networks with the...
Elias Gyftodimos, Peter A. Flach
WINE
2005
Springer
179views Economy» more  WINE 2005»
14 years 3 months ago
A Graph-Theoretic Network Security Game
Consider a network vulnerable to viral infection. The system security software can guarantee safety only to a limited part of the network. Such limitations result from economy cos...
Marios Mavronicolas, Vicky G. Papadopoulou, Anna P...
ECCC
2010
124views more  ECCC 2010»
13 years 10 months ago
Lower Bounds and Hardness Amplification for Learning Shallow Monotone Formulas
Much work has been done on learning various classes of "simple" monotone functions under the uniform distribution. In this paper we give the first unconditional lower bo...
Vitaly Feldman, Homin K. Lee, Rocco A. Servedio
ALT
1997
Springer
14 years 1 months ago
Learning One-Variable Pattern Languages Very Efficiently on Average, in Parallel, and by Asking Queries
A pattern is a string of constant and variable symbols. The language generated by a pattern is the set of all strings of constant symbols which can be obtained from by substituti...
Thomas Erlebach, Peter Rossmanith, Hans Stadtherr,...