Normalized Cut is a widely used technique for solving a
variety of problems. Although finding the optimal normalized
cut has proven to be NP-hard, spectral relaxations can
be ap...
Linli Xu (University of Alberta), Wenye Li (Univer...
—This paper proposes a framework for single-image super-resolution. The underlying idea is to learn a map from input low-resolution images to target high-resolution images based ...
ACT This works considers the problem of efficient energy allocation of resources in a continuous fashion in determining the location of targets in a sparse environment. We extend ...
We present a new approach to reinforcement learning in which the policies considered by the learning process are constrained by hierarchies of partially specified machines. This ...
Many applications of supervised learning require good generalization from limited labeled data. In the Bayesian setting, we can try to achieve this goal by using an informative pr...