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MLDM
2005
Springer
14 years 1 months ago
Using Clustering to Learn Distance Functions for Supervised Similarity Assessment
Assessing the similarity between objects is a prerequisite for many data mining techniques. This paper introduces a novel approach to learn distance functions that maximizes the c...
Christoph F. Eick, Alain Rouhana, Abraham Bagherje...
TCC
2009
Springer
141views Cryptology» more  TCC 2009»
14 years 8 months ago
Weak Verifiable Random Functions
Verifiable random functions (VRFs), introduced by Micali, Rabin and Vadhan, are pseudorandom functions in which the owner of the seed produces a public-key that constitutes a commi...
Zvika Brakerski, Shafi Goldwasser, Guy N. Rothblum...
FSE
2007
Springer
101views Cryptology» more  FSE 2007»
14 years 1 months ago
Generalized Correlation Analysis of Vectorial Boolean Functions
We investigate the security of n-bit to m-bit vectorial Boolean functions in stream ciphers. Such stream ciphers have higher throughput than those using single-bit output Boolean f...
Claude Carlet, Khoongming Khoo, Chu-Wee Lim, Chuan...
TIT
1998
96views more  TIT 1998»
13 years 7 months ago
Sequential Prediction of Individual Sequences Under General Loss Functions
Abstract— We consider adaptive sequential prediction of arbitrary binary sequences when the performance is evaluated using a general loss function. The goal is to predict on each...
David Haussler, Jyrki Kivinen, Manfred K. Warmuth
CORR
2010
Springer
142views Education» more  CORR 2010»
13 years 6 months ago
HyperANF: Approximating the Neighbourhood Function of Very Large Graphs on a Budget
The neighbourhood function NG(t) of a graph G gives, for each t ∈ N, the number of pairs of nodes x, y such that y is reachable from x in less that t hops. The neighbourhood fun...
Paolo Boldi, Marco Rosa, Sebastiano Vigna