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FOCS
2004
IEEE
13 years 8 months ago
Worst-Case to Average-Case Reductions Based on Gaussian Measures
We show that finding small solutions to random modular linear equations is at least as hard as approximating several lattice problems in the worst case within a factor almost line...
Daniele Micciancio, Oded Regev
APPROX
2007
Springer
104views Algorithms» more  APPROX 2007»
13 years 10 months ago
Worst-Case to Average-Case Reductions Revisited
Abstract. A fundamental goal of computational complexity (and foundations of cryptography) is to find a polynomial-time samplable distribution (e.g., the uniform distribution) and...
Dan Gutfreund, Amnon Ta-Shma
FOCS
2003
IEEE
13 years 9 months ago
On Worst-Case to Average-Case Reductions for NP Problems
We show that if an NP-complete problem has a non-adaptive self-corrector with respect to a samplable distribution then coNP is contained in NP/poly and the polynomial hierarchy co...
Andrej Bogdanov, Luca Trevisan
JC
2008
128views more  JC 2008»
13 years 4 months ago
Lattice rule algorithms for multivariate approximation in the average case setting
We study multivariate approximation for continuous functions in the average case setting. The space of d variate continuous functions is equipped with the zero mean Gaussian measu...
Frances Y. Kuo, Ian H. Sloan, Henryk Wozniakowski
STACS
1999
Springer
13 years 8 months ago
A Complete and Tight Average-Case Analysis of Learning Monomials
Abstract. We advocate to analyze the average complexity of learning problems. An appropriate framework for this purpose is introduced. Based on it we consider the problem of learni...
Rüdiger Reischuk, Thomas Zeugmann