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As it has become easier and cheaper to collect big datasets in the last few decades, designing efficient and low-cost algorithms for these datasets has attracted unprecedented attention. However, in most applications, even storing datasets as acquired has ...
Locality-Sensitive Hashing (LSH) approximates nearest neighbors in high dimensions by projecting original data into low-dimensional subspaces. The basic idea is to hash data samples to ensure that the probability of collision is much higher for samples tha ...
In the field of ITS applications evaluation, micro- simulation is becoming more and more a useful and powerful tool. In the evaluation process, one of the most important steps is the safety analysis. For that purpose, classical micro- simulation outputs gi ...
This thesis describes our research results in the context of peer-to-peer information retrieval (P2P-IR). One goal in P2P-IR is to build a search engine for the World Wide Web (WWW) that runs on up to hundreds of thousands or even millions computers distri ...
In-memory databases rely on pointer-intensive data structures to quickly locate data in memory. A single lookup operation in such data structures often exhibits long-latency memory stalls due to dependent pointer dereferences. Hiding the memory latency by ...
Network tomography infers internal network characteristics by sending and collecting probe packets from the network edge. Traditional tomographic techniques for general topologies typically use a mesh of multicast trees and/or unicast paths to cover the en ...
We propose a novel framework for blockcipher-based double-length hash functions by extending the recent generalization presented by Stam at FSE '09 for single-call hash functions. We focus on compression functions compressing 3n bits to 2n bits that use on ...
Springer-Verlag New York, Ms Ingrid Cunningham, 175 Fifth Ave, New York, Ny 10010 Usa2009
For several decades, online transaction processing has been one of the main applications that drives innovations in the data management ecosystem, and in turn the database and computer architecture communities. Despite the novel approaches from industry an ...
In this paper we consider distributed K-Nearest Neighbor (KNN) search and range query processing in high dimensional data. Our approach is based on Locality Sensitive Hashing (LSH) which has proven very efficient in answering KNN queries in centralized set ...
