Higher inductive types (HITs) in Homotopy Type Theory (HoTT) allow the definition of datatypes which have constructors for equalities over the defined type. HITs generalise quotient types, and allow to define types which are not sets in the sense of HoTT (i.e. do not satisfy uniqueness of equality proofs) such as spheres, suspensions and the torus. However, there are also interesting uses of HI...

This paper describes the robust optimal incremental motion control of a current  sensorless synchronous reluctance motor (SynRM), which can be specified by any desired speed profile. The control scheme is a combination of conventional linear quadratic (LQ) feedback control method and sliding mode control (SMC). A novel sliding switching surface is employed first, that makes the states of the Sy...

We calculate the broadband radio–X-ray spectra predicted by microblazar and microquasar models for Ultra-Luminous X-ray sources (ULXs), exploring the possibility that their dominant power-law component is produced by a relativistic jet, even at near-Eddington mass accretion rates. We do this by first constructing a generalized disk–jet theoretical framework in which some fraction of the total a...

In this paper, we discuss a technique for handling multi-class problems with binary classifiers, namely to learn one classifier for each pair of classes. Although this idea is known in the literature, it has not yet been thoroughly investigated in the context of inductive rule learning. We present an empirical evaluation of the method as a wrapper around the Ripper rule learning algorithm on 20...

Labelling problems for graphs consist in building distributed data structures, making it possible to check a given graph property or to compute a given function, the arguments of which are vertices. For an inductively computable function D, if G is a graph with n vertices and of clique-width at most k, where k is fixed, we can associate with each vertex x of G a piece of information (bit sequen...

Abstract This introduction consists of two parts. In the first part, special issue editors introduce inductive metaphysics from a historical as well systematic point view and discuss what distinguishes it other modern approaches to metaphysics. second they give brief summary individual articles in this issue.

This paper suggests that it may be easier to learn several hard tasks at one time than to learn these same tasks separately. In effect, the information provided by the training signal for each task serves as a domain-specific inductive bias for the other tasks. Frequently the world gives us clusters of related tasks to learn. When it does not, it is often straightforward to create additional ta...