We study online bounded space bin packing in the resource
augmentation model of competitive analysis.
In this model, the online bounded space packing algorithm has
to pack a list L of items in (0,1] into a small number of
bins of size b>=1.
Its performance is measured by comparing the ...
more >>>
We derive results of the following flavor:
If a combinatorial optimization problem can be formulated via a dynamic
program of a certain structure and if the involved cost and transition
functions satisfy certain arithmetical and structural conditions, then
the optimization problem automatically possesses a fully polynomial time
approximation scheme (FPTAS).
The majority of results in computational learning theory
are concerned with concept learning, i.e. with the special
case of function learning for classes of functions
with range {0,1}. Much less is known about the theory of
learning functions with a larger range such
as N or R. In ...
more >>>
