Gradient-following learning methods can encounter problems of implementation in many applications, and stochastic variants are frequently used to overcome these difficulties. We ...
— Many network operators offer some type of tiered service, in which users may select only from a small set of service levels (tiers). Such a service has the potential to simplif...
This paper is an empirical investigation into the effectiveness of linear scaling adaptation for case-based software project effort prediction. We compare two variants of a linea...
Colin Kirsopp, Emilia Mendes, Rahul Premraj, Marti...
Support vector machines are trained by solving constrained quadratic optimization problems. This is usually done with an iterative decomposition algorithm operating on a small wor...
We introduce the problem of query decomposition, where we are given a query and a document retrieval system, and we want to produce a small set of queries whose union of resulting...
Francesco Bonchi, Carlos Castillo, Debora Donato, ...