Over the past decade, the number of security attacks on IT and communications systems has risen drastically and as a result, security assurance has become a central issue for network operators and the telecommunications industry. Using a security assurance methodology at every stage of product development, vendors can show that the implementation of security assurance protocols in their products is accordance with agreed guidelines.
With the right partnership, managed services can help businesses to forge a path forward, creating a truly customer experience-centric operation built on superior network performance.
Across domains, many machine learning problems involve data which naturally comprises multiple views. Multi-view Learning is a machine learning technique that can utilize multiple views. Here we focus on co-training style multi-view learning algorithm under semi-supervised conditions which leverages both labeled and unlabeled data. In many domains, amount of (unlabeled) data available is very huge in size, which makes it impossible to learn serially in a single machine. In this work, we study various distributed multi-view learning using both consensus and complementary principles. We also propose an efficient computational design on Hadoop for learning multiple classifiers.
Roger Lanctot, leading Automotive analyst at Strategy Analytics, explains how Ericsson’s Connected Vehicle Cloud solution with Volvo Cars is differentiated.
Gunnar Mildh, Expert in the area of Radio Network Architecture at Ericsson Research describes how WiFi and Cellular integration will improve the end user experience.