This work provides a framework for learning sequential attention in real-world visual object recognition, using an architecture of three processing stages. The first stage rejects...
We present a search space analysis and its application in improving local search algorithms for the graph coloring problem. Using a classical distance measure between colorings, w...
Daniel Cosmin Porumbel, Jin-Kao Hao, Pascale Kuntz
This paper studies scalable data delivery algorithms in mobile ad hoc sensor networks with node and link failures. Many algorithms have been developed for data delivery and fusion...
Bin Yu, Paul Scerri, Katia P. Sycara, Yang Xu, Mic...
Policy gradient (PG) reinforcement learning algorithms have strong (local) convergence guarantees, but their learning performance is typically limited by a large variance in the e...
The search space of Bayesian Network structures is usually defined as Acyclic Directed Graphs (DAGs) and the search is done by local transformations of DAGs. But the space of Baye...