Hybrid learning methods use theoretical knowledge of a domain and a set of classified examples to develop a method for accurately classifying examples not seen during training. The challenge of hybrid learning systems is to use the information provided by one source of information to offset information missing from the other source. By so doing, a hybrid learning system should learn more effect...

With the emergence of connected and autonomous vehicles, sensors are increasingly deployed within cars to support new functionalities. Traffic generated by these sensors congest traditional intra-car networks, such as CAN buses. Furthermore, the large amount of wires needed to connect sensors makes it harder to design cars in a modular way. To alleviate these limitations, we propose, simulate, ...

How do gene regulatory networks evolve? A new study in yeasts shows that cis- and trans-regulatory changes resulted in a hybrid state of coexisting ancestral and derived regulatory circuits. This hybrid state then diversified into a variety of modern networks.

Probabilistic logical models have proven to be very successful at modelling uncertain, complex relational data. Most current formalisms and implementations focus on modelling domains that only have discrete variables. Yet many real-world problems are hybrid and have both discrete and continuous variables. In this paper we focus on the Logical Bayesian Network (LBN) formalism. This paper discuss...

Recently, neural networks have become a very important method in the field of medical diagnostic. The objective of this work is to diagnose hepatitis disease by using different neural network architectures. Standard feedforward networks and a hybrid network were investigated. Results obtained show that especially the hybrid network can be successfully used for diagnosing of hepatitis.

This paper introduces the hybrid copula Bayesian network (HCBN) model, a generalization of the copula Bayesian network (CBN) model developed by Elidan (2010) for continuous random variables to multivariate mixed probability distributions of discrete and continuous random variables. To this end, we extend the theorems proved by Nešlehová (2007) from bivariate to multivariate copulas with discret...

The rate at which information can be exchanged between nodes in a hybrid network is investigated. The network includes n ad hoc nodes and b base stations, where the ad hoc nodes can share information through the wired infrastructure in addition to wireless ad hoc communication. The per-node throughput scaling achievable in this hybrid network as n (and b) grows was studied in previous work for ...

We present a hybrid system based on a combination of Neural Networks and rule-based matching systems that is capable of detecting network-initiated intrusion attacks on web servers. The system has a strong learning component allowing it to recognize even novel attacks (i.e. attacks it has never seen before) and categorize them as such. The performance of the Neural Network in detecting attacks ...