Anomaly detection in multivariate time series is an important data mining task with applications to ecosystem modeling, network traffic monitoring, medical diagnosis, and other d...
Christopher Potter, Haibin Cheng, Pang-Ning Tan, S...
In this work we present a method to perform a complete audiovisual source separation without need of previous information. This method is based on the assumption that sounds are c...
Anna Llagostera Casanovas, Gianluca Monaci, Pierre...
While exploring to nd better solutions, an agent performing online reinforcement learning (RL) can perform worse than is acceptable. In some cases, exploration might have unsafe, ...
Satinder P. Singh, Andrew G. Barto, Roderic A. Gru...
Abstract. We present a symbolic framework, based on a modular operational semantics, for formalizing different notions of compromise relevant for the analysis of cryptographic prot...
We present a formal framework for notions related to testing and model based test generation for a behavioural subset of UML Statecharts (UMLSCs). This framework builds, on one ha...