Towards QoS-Based Embedded Machine Learning

Towards Real-Time Machine Learning

Mining data streams has become an important topic within the last decade, and numerous approaches have addressed various issues in this domain. However, little work has been devoted to the setting where high-speed data streams are potentially faster than the underlying learning algorithm, and nevertheless a prediction needs to be given promptly for each unlabeled instance in the stream. Additio...

Towards Intelligent Machine Learning Algorithms

Towards Practical Machine Learning Techniques

Most research on the application of machine learning to engineering problems have solved artiicial problems. While research claimed to have reached results that would improve practice, these results have never been put to work by engineers themselves in solving their problems. A diierent approach of doing research on machine learning application is presented and a system design that may result ...

Towards a Biomolecular Learning Machine

Learning and generalisation are fundamental behavioural traits of intelligent life. We present a synthetic biochemical circuit which can exhibit nontrivial learning and generalisation behaviours, which is a first step towards demonstrating that these behaviours may be realised at the molecular level. The aim of our system is to learn positive real-valued weights for a real-valued linear functio...

Towards Geo-Distributed Machine Learning

Latency to end-users and regulatory requirements push large companies to build data centers all around the world. The resulting data is “born” geographically distributed. On the other hand, many machine learning applications require a global view of such data in order to achieve the best results. These types of applications form a new class of learning problems, which we call Geo-Distributed Ma...