The asymptotic behavior of stochastic gradient algorithms is studied. Relying on some results of differential geometry (Lojasiewicz gradient inequality), the almost sure pointconve...
Associative classification is a rule-based approach to classify data relying on association rule mining by discovering associations between a set of features and a class label. Su...
Background: Empirical binding models have previously been investigated for the energetics of protein complexation (G models) and for the influence of mutations on complexation (i....
This paper presents a new automated model-driven technique to generate test cases by using feedback from the execution of a "seed test suite" on an application under tes...
Comparing and contrasting is an important strategy people employ to understand new situations and create solutions for new problems. Similar events can provide hints for problem s...