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Università degli Studi di Siena

Università Degli Studi Di Perugia

A Support Vector Machine (SVM ) is a powerful classifier method, already used in many problems, which can be viewed as a learning problem bringing to a convex optimization. In recent years, a considerable attention has been given on semisupervised learning, differing from traditional supervised learning by making use of unlabeled data. In fact, in many applications, labeling examples may cost l...

Università degli Studi di Padova Dipartimento di Ingegneria dell ’ Informazione

In this thesis, I propose a robust and easy to implement method to calibrate an IMU without any external equipment. The procedure is based on a multi-position scheme, providing scale and misalignments factors for both the accelerometers and gyroscopes triads, while estimating the sensor biases. The method only requires the sensor to be moved by hand and placed in a set of different, static posi...

Università degli Studi di Verona Dipartimento di Informatica

Functions We already observed in Section 5.2.2 that a function f : Z → Z is decomposed into elementary functions, i.e., assembly instructions within some basic block. Following the same approach, let us assume that the function f can be expressed as a composition of elementary functions, namely f = λx.h(g1(x, ..., x), ..., gk(x, ..., x)) where h : Zk → Z and gi : Zni → Z. More in general, each ...

Università degli Studi di Bologna