1.

Record Nr.

UNISA996464444703316

Titolo

Machine Learning and Knowledge Discovery in Databases [[electronic resource] ] : European Conference, ECML PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings, Part I / / edited by Frank Hutter, Kristian Kersting, Jefrey Lijffijt, Isabel Valera

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021

ISBN

3-030-67658-7

Edizione

[1st ed. 2021.]

Descrizione fisica

1 online resource (L, 764 p. 219 illus., 188 illus. in color.)

Collana

Lecture Notes in Artificial Intelligence, , 2945-9141 ; ; 12457

Disciplina

006.312

Soggetti

Data mining

Data structures (Computer science)

Information theory

Machine learning

Social sciences—Data processing

Computer vision

Data Mining and Knowledge Discovery

Data Structures and Information Theory

Machine Learning

Computer Application in Social and Behavioral Sciences

Computer Vision

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

Pattern Mining -- clustering -- privacy and fairness -- (social) network analysis and computational social science -- dimensionality reduction and autoencoders -- domain adaptation -- sketching, sampling, and binary projections -- graphical models and causality -- (spatio-) temporal data and recurrent neural networks -- collaborative filtering and matrix completion.

Sommario/riassunto

The 5-volume proceedings, LNAI 12457 until 12461 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2020, which was



held during September 14-18, 2020. The conference was planned to take place in Ghent, Belgium, but had to change to an online format due to the COVID-19 pandemic. The 232 full papers and 10 demo papers presented in this volume were carefully reviewed and selected for inclusion in the proceedings. The volumes are organized in topical sections as follows: Part I: Pattern Mining; clustering; privacy and fairness; (social) network analysis and computational social science; dimensionality reduction and autoencoders; domain adaptation; sketching, sampling, and binary projections; graphical models and causality; (spatio-) temporal data and recurrent neural networks; collaborative filtering and matrix completion. Part II: deep learning optimization and theory; active learning; adversarial learning; federated learning; Kernel methods and online learning; partial label learning; reinforcement learning; transfer and multi-task learning; Bayesian optimization and few-shot learning. Part III: Combinatorial optimization; large-scale optimization and differential privacy; boosting and ensemble methods; Bayesian methods; architecture of neural networks; graph neural networks; Gaussian processes; computer vision and image processing; natural language processing; bioinformatics. Part IV: applied data science: recommendation; applied data science: anomaly detection; applied data science: Web mining; applied data science: transportation; applied data science: activity recognition; applied data science: hardware and manufacturing; applied data science: spatiotemporal data. Part V: applied data science: social good; applied data science: healthcare; applied data science: e-commerce and finance; applied data science: computational social science; applied data science: sports; demo track. .



2.

Record Nr.

UNINA9910704753603321

Titolo

Defense infrastructure : improved guidance needed for estimating alternatively financed project liabilities : report to congressional committees

Pubbl/distr/stampa

[Washington, D.C.] : , : United States Government Accountability Office, , 2013

Descrizione fisica

1 online resource (ii, 74 pages) : illustrations

Soggetti

Military base closures

Military base closures - Economic aspects - United States

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Title from title screen (viewed July 8, 2013).

"April 2013."

"GAO-13-337."

Nota di bibliografia

Includes bibliographical references.



3.

Record Nr.

UNIORUON00100222

Autore

RAMAGE, Edwin S.

Titolo

Roman satirists and their satire / Edwin S. Ramage, David L. Sigsbee, Sigmund C. Fredericks

Pubbl/distr/stampa

New Jersey, : Noyes Press, 1974

Descrizione fisica

p. ;  cm

Altri autori (Persone)

FREDERICKS, Sigmund C.

SIGSBEE, David L.

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia