Motivated by applications of rateless coding, decision feedback, and automatic repeat request (ARQ), we study the problem of universal decoding for unknown channels in the presence...
The aim of the paper is to introduce general techniques in order to optimize the parallel execution time of sorting on a distributed architectures with processors of various speeds...
We describe a novel inference algorithm for sparse Bayesian PCA with a zero-norm prior on the model parameters. Bayesian inference is very challenging in probabilistic models of t...
It is well known that exploiting label correlations is important for multi-label learning. Existing approaches typically exploit label correlations globally, by assuming that the ...
In this paper, we explore a hybrid global/local search optimization framework for dynamic voltage scaling in embedded multiprocessor systems. The problem is to find, for a multipr...