In this paper, we present a framework for the design of steganographic schemes that can provide provable security by achieving zero Kullback-Leibler divergence between the cover a...
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
Efficient and expressive comparison of sequences is an essential procedure for learning with sequential data. In this article we propose a generic framework for computation of sim...
The design and evaluation of microprocessor architectures is a difficult and time-consuming task. Although small, handcoded microbenchmarks can be used to accelerate performance e...
Speculation is an every day phenomenon whereby one acts in anticipation of particular conditions that are likely to hold in the future. Computer science research has seen many suc...