Manifold learning methods are promising data analysis tools. However, if we locate a new test sample on the manifold, we have to find its embedding by making use of the learned e...
As chip multiprocessors (CMPs) become increasingly mainstream, architects have likewise become more interested in how best to share a cache hierarchy among multiple simultaneous t...
Lisa R. Hsu, Steven K. Reinhardt, Ravishankar R. I...
We propose a general method that parameterizes general surfaces with complex (possible branching) topology using Riemann surface structure. Rather than evolve the surface geometry...
Yalin Wang, Xianfeng Gu, Kiralee M. Hayashi, Tony ...
Failures of any type are common in current datacenters, partly due to the higher scales of the data stored. As data scales up, its availability becomes more complex, while differe...
Nicolas Bonvin, Thanasis G. Papaioannou, Karl Aber...
We consider the problem of computing all-pair correlations in a warehouse containing a large number (e.g., tens of thousands) of time-series (or, signals). The problem arises in a...