Dynamic Bayesian networks (DBNs) offer an elegant way to integrate various aspects of language in one model. Many existing algorithms developed for learning and inference in DBNs ...
Efforts to achieve the long-standing dream of realizing scalable learning algorithms for networks of spiking neurons in silicon have been hampered by (a) the limited scalability of...
Jae-sun Seo, Bernard Brezzo, Yong Liu, Benjamin D....
The availability of whole genome sequences and high-throughput genomic assays opens the door for in silico analysis of transcription regulation. This includes methods for discover...
Yoseph Barash, Gal Elidan, Nir Friedman, Tommy Kap...
An accurate mapping of traffic to applications is important for a broad range of network management and measurement tasks. Internet applications have traditionally been identifi...
Patrick Haffner, Subhabrata Sen, Oliver Spatscheck...
A variety of remote sensing attacks allow adversaries to break flow confidentiality and gather mission-critical information in distributed systems. Such attacks are easily supple...