For modeling and analyzing regulatory networks based on qualitative information and possibly additional temporal constraints, approaches using hybrid automata can be very helpful. ...
In this chapter, we describe a view of statistical learning in the inductive logic programming setting based on kernel methods. The relational representation of data and background...
This paper proposes novel hierarchical self-organizing associative memory architecture for machine learning. This memory architecture is characterized with sparse and local interco...
In this paper we present the distributed event localization and tracking algorithm DELTA that solely depends on light measurements. Based on this information and the positions of t...
This paper presents adaptive resource sharing model that uses a revenue criterion to allocate network resources in an optimal way. The model ensures QoS requirements of data flow...
Jyrki Joutsensalo, Ari Viinikainen, Mika Wikstr&ou...