We claim and present arguments to the effect that a large class of manifold learning algorithms that are essentially local and can be framed as kernel learning algorithms will suf...
—This paper explores how to remotely monitor network-wide quality in mesh-pull P2P live streaming systems. Peers in such systems advertise to each other buffer maps which summari...
Efficient access methods are reviewed and explored in relation to the global surface hourly data set and several of its derivative products. Typical access paradigms are compared ...
This paper describes the AccuPower toolset -- a set of simulation tools accurately estimating the power dissipation within a superscalar microprocessor. AccuPower uses a true hard...
Abstract— This paper discusses the generation of informationrich, arbitrarily-large synthetic data sets which can be used to (a) efficiently learn tests that correlate a set of ...
Haralampos-G. D. Stratigopoulos, Salvador Mir, Yio...