Decreasing disk costs have made it practical to retain longlived snapshots, enabling new applications that analyze past states and infer about future states. Current approaches of...
We cast model-free reinforcement learning as the problem of maximizing the likelihood of a probabilistic mixture model via sampling, addressing both the infinite and finite horizo...
In this paper, we discuss a technique for handling multi-class problems with binary classifiers, namely to learn one classifier for each pair of classes. Although this idea is kno...
The goal of this paper is to investigate the impact of dictionary choosing for a total variation dictionary model. After theoretical analysis, we present the experiments in which ...
— Multi-slot resource scheduling in a general two dimensional wireless ad hoc network, is a hard problem with no known polynomial-time solution. Recent optimization theoretic ana...