1.

Record Nr.

UNISA996465642703316

Titolo

Towards Integrative Machine Learning and Knowledge Extraction [[electronic resource] ] : BIRS Workshop, Banff, AB, Canada, July 24-26, 2015, Revised Selected Papers / / edited by Andreas Holzinger, Randy Goebel, Massimo Ferri, Vasile Palade

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017

ISBN

3-319-69775-7

Edizione

[1st ed. 2017.]

Descrizione fisica

1 online resource (XVI, 207 p. 57 illus.)

Collana

Lecture Notes in Artificial Intelligence ; ; 10344

Disciplina

006.3

Soggetti

Artificial intelligence

Computers

Mathematical statistics

Software engineering

Computer organization

Artificial Intelligence

Information Systems and Communication Service

Probability and Statistics in Computer Science

Software Engineering/Programming and Operating Systems

Computer Systems Organization and Communication Networks

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Includes index.

Nota di contenuto

Towards integrative Machine Learning & Knowledge Extraction -- Machine Learning and Knowledge Extraction in Digital Pathology needs an integrative approach -- Comparison of Public-Domain Software and Services for Probabilistic Record Linkage and Address Standardization -- Better Interpretable Models for Proteomics Data Analysis Using rule-based Mining -- Probabilistic Logic Programming in Action -- Persistent topology for natural data analysis — A survey -- Predictive Models for Differentiation between Normal and Abnormal EEG through Cross-Correlation and Machine Learning Techniques -- A Brief Philosophical Note on Information -- Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline -- A Fast



Semi-Automatic Segmentation Tool for Processing Brain Tumor Images -- Topological characteristics of oil and gas reservoirs and their applications -- Convolutional and Recurrent Neural Networks for Activity Recognition in Smart Environment.

Sommario/riassunto

The BIRS Workshop “Advances in Interactive Knowledge Discovery and Data Mining in Complex and Big Data Sets” (15w2181), held in July 2015 in Banff, Canada, was dedicated to stimulating a cross-domain integrative machine-learning approach and appraisal of “hot topics” toward tackling the grand challenge of reaching a level of useful and useable computational intelligence with a focus on real-world problems, such as in the health domain. This encompasses learning from prior data, extracting and discovering knowledge, generalizing the results, fighting the curse of dimensionality, and ultimately disentangling the underlying explanatory factors in complex data, i.e., to make sense of data within the context of the application domain.  The workshop aimed to contribute advancements in promising novel areas such as at the intersection of machine learning and topological data analysis. History has shown that most often the overlapping areas at intersections of seemingly disparate fields are key for the stimulation of new insights and further advances. This is particularly true for the extremely broad field of machine learning.



2.

Record Nr.

UNISA996385468703316

Autore

Mandeville John, Sir.

Titolo

The voyages and trauailes of Sir John Maundeuile knight [[electronic resource] ] : Wherein is treated of the way towards Hierusalem, and of the meruailes of Inde, with other lands and countries

Pubbl/distr/stampa

London, : Printed by Thomas Este, [1582?]

Descrizione fisica

[160] p. : ill

Soggetti

Voyages and travels

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Attributed to John Mandeville, but in fact an English version of a text known as "Itinerarium". The original was probably written in Anglo-Norman French and has been attributed to Jean d'Outremeuse.

Publication date suggested by STC.

With an index.

Signatures: A-U⁴ (U4 blank).

Reproduction of the original in the Bodleian Library.

Sommario/riassunto

eebo-0014