Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...
Abstract--This paper presents a novel and domainindependent approach for graph-based structure learning. The approach is based on solving the Maximum Common SubgraphIsomorphism pro...
Abstract. With increasing volumes of data, much effort has been devoted to finding the most suitable answer to an information need. However, in many domains, the question whether a...
Abstract--It is critical to use automated generators for synthetic models and data, given the sparsity of benchmark models for empirical analysis and the cost of generating models ...
Abstract--Frame detection and timing acquisition are challenging tasks in orthogonal frequency-division multiplexing systems plagued by narrowband interference (NBI). Most existing...
Luca Sanguinetti, Michele Morelli, H. Vincent Poor