The problem of characterizing learnability is the most basic question of statistical learning theory. A fundamental and long-standing answer, at least for the case of supervised c...
The newly emerging field of Network Science deals with the tasks of modelling, comparing and summarizing large data sets that describe complex interactions. Because pairwise affin...
The last decade has witnessed the emergence of the application-specific instruction-set processor (ASIP) as a viable platform for embedded systems. Extensible ASIPs allow the user ...
Aggregate traffic loads and topology in multi-hop wireless networks may vary slowly, permitting MAC protocols to `learn' how to spatially coordinate and adapt contention patte...
A parametric generalized likelihood ratio test (GLRT) for multichannel signal detection in spatially and temporally colored disturbance was recently introduced by modeling the dist...