We consider the problem of numerical stability and model density growth when training a sparse linear model from massive data. We focus on scalable algorithms that optimize certain...
A common task of recommender systems is to improve customer experience through personalized recommendations based on prior implicit feedback. These systems passively track differe...
Motivated by an underground mining operation at Kiruna, Sweden, we formulate a mixed integer program to schedule iron ore production over multiple time periods. Our optimization m...
Large-scale Parallel Web Search Engines (WSEs) needs to adopt a strategy for partitioning the inverted index among a set of parallel server nodes. In this paper we are interested ...
In this paper we: introduce EMADS, the Extendible Multi-Agent Data mining System, to support the dynamic creation of communities of data mining agents; explore the capabilities of ...