In multiple instance learning (MIL), how the instances determine the bag-labels is an essential issue, both algorithmically and intrinsically. In this paper, we show that the mech...
In this paper, we present two techniques to analyze greedy approximation with nonsubmodular functions restricted submodularity and shifted submodularity. As an application of the ...
Ding-Zhu Du, Ronald L. Graham, Panos M. Pardalos, ...
The Distributed Object Group Framework(DOGF) we constructed supports the grouping of distributed objects that are required for distributed application. From the DOGF, we manage dis...
In many applications one is concerned with the approximation of functions from a finite set of scattered data sites with associated function values. We describe a scheme for cons...
We present a model of adaptive attacks which we combine with information-theoretic metrics to quantify the information revealed to an adaptive adversary. This enables us to expres...