We study sparse principal components analysis in the high-dimensional setting, where p (the number of variables) can be much larger than n (the number of observations). We prove o...
We present a new open source toolkit for phrase-based and syntax-based machine translation. The toolkit supports several state-of-the-art models developed in statistical machine t...
In this paper, we propose a robust model selection criterion for mixtures of subspaces called minimum effective dimension (MED). Previous information-theoretic model selection cri...
The process of computing the physical locations of nodes in a wireless sensor network is known as localization. Selflocalization is critical for large-scale sensor networks becaus...
In the past few years since Adleman’s pioneering work on solving the HPP(Hamiltonian Path Problem) with a DNA-based computer [1], many algorithms have been designed on solving NP...