This paper presents an efficient technique for energy minimisation based on dynamically variable supply voltages. The efficiency is achieved by considering that power consumed by the core depends on the computation carried out on it. Energy is further minimised by allowing the voltage supply to vary continuously. The computational delay introduced due to supply voltage reduction is tolerated by...

In this paper we formulate in general terms an approach to prove strong consistency of the Empirical Risk Minimisation inductive principle applied to the prototype or distance based clustering. This approach was motivated by the Divisive Information-Theoretic Feature Clustering model in probabilistic space with Kullback-Leibler divergence which may be regarded as a special case within the Clust...

A calculus of events is presented in which domain constraints, concurrent events, and events with non-deterministic effects can be represented. The paper offers a non-monotonic solution to the frame problem for this formalism that combines two of the techniques developed for the situation calculus, namely causal and state-based minimisation. A theorem is presented which guarantees that temporal...

This article treats the problem of learning a dictionary providing sparse representations for a given signal class, via l1 minimisation. The problem is to identify a dictionary Φ from a set of training samples Y knowing that Y = ΦX for some coefficient matrix X. Using a characterisation of coefficient matrices X that allow to recover any basis as a local minimum of an l1 minimisation problem, i...

Data minimisation is a privacy-enhancing principle considered as one of the pillars of personal data regulations. This principle dictates that personal data collected should be no more than necessary for the specific purpose consented by the user. In this paper we study data minimisation from a programming language perspective. We define a data minimiser as a pre-processor for the input which r...