Abstract. The ability to cooperate on common tasks in a distributed setting is key to solving a broad range of computation problems ranging from distributed search such as SETI to ...
Chryssis Georgiou, Alexander Russell, Alexander A....
Abstract. We consider the problem of encoding a graph with n vertices and m edges compactly supporting adjacency, neighborhood and degree queries in constant time in the log n-bit ...
embedded in a sliding-window scheme. Such exhaustive
search involves massive computation. Efficient Subwindow
Search (ESS) [11] avoids this by means of branch
and bound. However...
Modeling consistency of style in isogenous fields of patterns (such as character patterns in a word from the same font or writer) can improve classification accuracy. Since such p...
Sampling is a popular way of scaling up machine learning algorithms to large datasets. The question often is how many samples are needed. Adaptive stopping algorithms monitor the ...