This thesis implements different approaches to predict the one-day ahead Value at Risk (VaR) of crude oil return data. The Historical Simulation (HS) approach, a non-parametric model, randomly resamples past observations ...

We introduce variable step size commutator free Lie group integrators, where the error control is achieved using embedded Runge–Kutta pairs. These are schemes for the integration of initial value problems posed on homogeneous ...

This paper concerns an optimization algorithm for unconstrained nonconvex problems where the objective function has sparse connections between the unknowns. The algorithm is based on applying a dissipation preserving ...

Laboratory studies on associations between disease resistance and susceptibility and major histocompatibility (MH) genes in Atlantic salmon Salmo salar have shown the importance of immunogenetics in understanding the ...

Time series generation (TSG) studies have mainly focused on the use of Generative Adversarial Networks (GANs) combined with recurrent neural network (RNN) variants. However, the fundamental limitations and challenges of ...

Mix nets are often used to provide privacy in modern security protocols, through shuffling. Some of the most important applications, such as secure electronic voting, require mix nets that are verifiable. In the literature, ...

In this work we present a new approach to verifiable decryption which converts a 2-party passively secure distributed decryption protocol into a 1-party proof of correct decryption. This leads to an efficient and simple ...

We describe the Verifiable Shuffled Decryption problem, and present five solutions based on adapting several existing verifiable shuffles. All but one may have potential for implementation, the choice of which would depend ...

In this paper, we obtain a vertical–horizontal decomposition formula of Laplacians on manifolds with a special foliation structure. Two Nomizu-type theorems for cohomologies of nilmanifolds follow as applications.

I dette prosjektet ble dyplæringsmodeller trent på Youtube-8M datasettet, som er et stort benchmark for for multi-label videoklassifisering, og evaluert ved hjelp av F1-score. De trente modellene brukte forskjellige metoder ...