In the online linear optimization problem, a learner must choose, in each round, a decision from a set D ⊂ Rn in order to minimize an (unknown and changing) linear cost function...
Background: Optimization theory has been applied to complex biological systems to interrogate network properties and develop and refine metabolic engineering strategies. For examp...
Erwin P. Gianchandani, Matthew A. Oberhardt, Antho...
In multi-instance learning, the training examples are bags composed of instances without labels, and the task is to predict the labels of unseen bags through analyzing the training...
Background: Regulatory regions that function in DNA replication and gene transcription contain specific sequences that bind proteins as well as less-specific sequences in which th...
Today, most multi-connected autonomous systems (AS) need to control the flow of their interdomain traffic for both performance and economical reasons. This is usually done by manu...