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FSTTCS
2009
Springer
16 years 27 days ago
Functionally Private Approximations of Negligibly-Biased Estimators
ABSTRACT. We study functionally private approximations. An approximation function g is functionally private with respect to f if, for any input x, g(x) reveals no more information ...
André Madeira, S. Muthukrishnan
SODA
2010
ACM
164views Algorithms» more  SODA 2010»
16 years 3 months ago
Differentially Private Approximation Algorithms
Consider the following problem: given a metric space, some of whose points are "clients," select a set of at most k facility locations to minimize the average distance f...
Anupam Gupta, Katrina Ligett, Frank McSherry, Aaro...
CIKM
2000
Springer
15 years 10 months ago
Dimensionality Reduction and Similarity Computation by Inner Product Approximations
—As databases increasingly integrate different types of information such as multimedia, spatial, time-series, and scientific data, it becomes necessary to support efficient retri...
Ömer Egecioglu, Hakan Ferhatosmanoglu
KDD
2006
ACM
153views Data Mining» more  KDD 2006»
16 years 6 months ago
Spatial scan statistics: approximations and performance study
Spatial scan statistics are used to determine hotspots in spatial data, and are widely used in epidemiology and biosurveillance. In recent years, there has been much effort invest...
Deepak Agarwal, Andrew McGregor, Jeff M. Phillips,...
ATAL
2007
Springer
16 years 16 days ago
Model-based function approximation in reinforcement learning
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Nicholas K. Jong, Peter Stone