We study the problem of data propagation in sensor networks, comprised of a large number of very small and low-cost nodes, capable of sensing, communicating and computing. The dis...
Ioannis Chatzigiannakis, Tassos Dimitriou, Sotiris...
We investigate the use of linear and nonlinear principal manifolds for learning low-dimensional representations for visual recognition. Several leading techniques: Principal Compo...
Background: Solexa/Illumina short-read ultra-high throughput DNA sequencing technology produces millions of short tags (up to 36 bases) by parallel sequencing-by-synthesis of DNA ...
Jacques Rougemont, Arnaud Amzallag, Christian Isel...
Background: Pairwise stochastic context-free grammars (Pair SCFGs) are powerful tools for evolutionary analysis of RNA, including simultaneous RNA sequence alignment and secondary...
We address the problem of unsupervised image auto-annotation with probabilistic latent space models. Unlike most previous works, which build latent space representations assuming ...