| |
|
|
|
|
|
|
|
|
1. |
Record Nr. |
UNISA990003461840203316 |
|
|
Autore |
LAOUREUX, Denis |
|
|
Titolo |
Maurice Maeterlinck et la dramaturgie de l'image : les arts et les lettres dans le symbolisme en Belgique / Denis Laoureux |
|
|
|
|
|
|
|
Pubbl/distr/stampa |
|
|
Brasschaat, : Pandora, 2008 |
|
|
|
|
|
|
|
ISBN |
|
978-905-325-8 |
97890-5325-287-1 |
|
|
|
|
|
|
|
|
Descrizione fisica |
|
287 p. : ill. in parte color. ; 24 cm |
|
|
|
|
|
|
Collana |
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
Soggetti |
|
Simbolismo <Movimenti artistici> - Belgio - Cataloghi di esposizioni |
Maeterlinck, Maurice Cataloghi di esposizioni |
|
|
|
|
|
|
|
|
Collocazione |
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
Note generali |
|
Cet ouvrage est publiè à l'occasion de l'Exposition "Le Musée Imaginaire de Maurice Maeterlinck" organisée au Musée Provincial Félicien Rops du 19 janvier au 13 avril 2008 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
2. |
Record Nr. |
UNISALENTO991002024819707536 |
|
|
Autore |
Gering, Jens |
|
|
Titolo |
Domitian, dominus et deus? : Herrschafts- und Machtstrukturen im Romischen Reich zur Zeit des letzten Flaviers / Jens Gering |
|
|
|
|
|
|
|
Pubbl/distr/stampa |
|
|
Rahden/Westf. : VML, Verlag Marie Leidorf, 2012 |
|
|
|
|
|
|
|
ISBN |
|
|
|
|
|
|
Descrizione fisica |
|
|
|
|
|
|
Collana |
|
Osnabrucker Forschungen zu Altertum und Antike-Rezeption ; 15 |
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
Soggetti |
|
Domiziano, Tito Flavio <Imperatore romano> |
Domiziano, Tito Flavio <Imperatore romano> |
Impero romano Storia Sec. 1. |
|
|
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
Nota di bibliografia |
|
Bibliografia: p. [380]-413. Indice |
|
|
|
|
|
|
|
|
|
|
|
|
|
3. |
Record Nr. |
UNINA9910299225203321 |
|
|
Autore |
Amini Massih-Reza |
|
|
Titolo |
Learning with Partially Labeled and Interdependent Data / / by Massih-Reza Amini, Nicolas Usunier |
|
|
|
|
|
|
|
Pubbl/distr/stampa |
|
|
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
|
|
|
|
|
|
|
|
|
ISBN |
|
|
|
|
|
|
Edizione |
[1st ed. 2015.] |
|
|
|
|
|
Descrizione fisica |
|
1 online resource (113 p.) |
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
|
|
Soggetti |
|
Artificial intelligence |
Data mining |
Statistics |
Artificial Intelligence |
Data Mining and Knowledge Discovery |
Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences |
|
|
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
Note generali |
|
Description based upon print version of record. |
|
|
|
|
|
|
Nota di bibliografia |
|
Includes bibliographical references and index. |
|
|
|
|
|
|
Nota di contenuto |
|
Introduction -- Introduction to learning theory -- Semi-supervised learning -- Learning with interdependent data. |
|
|
|
|
|
|
|
|
Sommario/riassunto |
|
This book develops two key machine learning principles: the semi-supervised paradigm and learning with interdependent data. It reveals new applications, primarily web related, that transgress the classical machine learning framework through learning with interdependent data. The book traces how the semi-supervised paradigm and the learning to rank paradigm emerged from new web applications, leading to a massive production of heterogeneous textual data. It explains how semi-supervised learning techniques are widely used, but only allow a limited analysis of the information content and thus do not meet the demands of many web-related tasks. Later chapters deal with the development of learning methods for ranking entities in a large |
|
|
|
|
|
|
|
|
|
|
collection with respect to precise information needed. In some cases, learning a ranking function can be reduced to learning a classification function over the pairs of examples. The book proves that this task can be efficiently tackled in a new framework: learning with interdependent data. Researchers and professionals in machine learning will find these new perspectives and solutions valuable. Learning with Partially Labeled and Interdependent Data is also useful for advanced-level students of computer science, particularly those focused on statistics and learning. |
|
|
|
|
|
| |