We describe an algorithm for computing planar convex hulls in the self-improving model: given a sequence I1, I2, . . . of planar n-point sets, the upper convex hull conv(I) of eac...
Kenneth L. Clarkson, Wolfgang Mulzer, C. Seshadhri
In our prior work, we introduced a generalization of the multiple-instance learning (MIL) model in which a bag's label is not based on a single instance's proximity to a...
We present a kernel-based recursive least-squares (KRLS) algorithm on a fixed memory budget, capable of recursively learning a nonlinear mapping and tracking changes over time. I...
Two mobile agents (robots) with distinct labels have to meet in an arbitrary, possibly infinite, unknown connected graph or in an unknown connected terrain in the plane. Agents ar...
We apply and extend the priority algorithm framework introduced by Borodin, Nielsen, and Rackoff to define "greedy-like" algorithms for the (uncapacitated) facility locat...