Motivated by a real-world problem, we study a novel budgeted optimization problem where the goal is to optimize an unknown function f(x) given a budget. In our setting, it is not ...
Javad Azimi, Xiaoli Fern, Alan Fern, Elizabeth Bur...
We present a novel portfolio selection technique, which replaces the traditional maximization of the utility function with a probabilistic approach inspired by statistical physics....
Robert Marschinski, Pietro Rossi, Massimo Tavoni, ...
Numerical possibility theory, belief function have been suggested as useful tools to represent imprecise, vague or incomplete information. They are particularly appropriate in unc...
It has been unclear whether optimal experimental design accounts of data selection may offer insight into evidence acquisition tasks in which the learner’s beliefs change greatl...
In this paper, we study a novel problem Collective Active Learning, in which we aim to select a batch set of "informative" instances from a networking data set to query ...