We examine the problem of retrieving the top-m ranked items from a large collection, randomly distributed across an n-node system. In order to retrieve the top m overall, we must ...
We present a new family of linear time algorithms based on sufficient statistics for string comparison with mismatches under the string kernels framework. Our algorithms improve t...
In this paper we study the spectrum of certain large random Hermitian Jacobi matrices. These matrices are known to describe certain communication setups. In particular we are inte...
Prototype selection problem consists of reducing the size of databases by removing samples that are considered noisy or not influential on nearest neighbour classification tasks. ...
In this work, we propose a new paradigm called power emulation, which exploits hardware acceleration to drastically speedup power estimation. Power emulation is based on the obser...