Searching approximate nearest neighbors in large scale high dimensional data set has been a challenging problem. This paper presents a novel and fast algorithm for learning binary...
Ray tracing and Monte-Carlo based global illumination, as well as radiosity and other finite-element based global illumination methods, all require repeated evaluation of quantita...
Yiorgos Chrysanthou, Daniel Cohen-Or, Dani Lischin...
The binary algorithm is a variant of the Euclidean algorithm that performs well in practice. We present a quasi-linear time recursive algorithm that computes the greatest common di...
The problem of finding a local minimum of a black-box function is central for understanding local search as well as quantum adiabatic algorithms. For functions on the Boolean hype...
Instance based locality optimization 6 is a semi automatic program restructuring method that reduces the number of cache misses. The method imitates the human approach of consideri...