We address the issue of compiling ML pattern matching to compact and efficient decisions trees. Traditionally, compilation to decision trees is optimized by (1) implementing decis...
The majority of the existing algorithms for learning decision trees are greedy--a tree is induced top-down, making locally optimal decisions at each node. In most cases, however, ...
The majority of the existing algorithms for learning decision trees are greedy--a tree is induced top-down, making locally optimal decisions at each node. In most cases, however, ...
This work presents decision trees adequate for the classification of series data. There are several methods for this task, but most of them focus on accuracy. One of the requirem...
Abstract. In peer-to-peer based live streaming systems, a great number of participants have to cooperate to efficiently and reliably distribute a continuous flow of data. Each rec...
Michael Brinkmeier, Mathias Fischer, Sascha Grau, ...