Brain injury : functional aspects, rehabilitation and prevention / / edited by Amit Agrawal

• Record Nr.: UNINA9910138259403321
• Pubbl/distr/stampa: Rijeka, Croatia : , : InTech, , [2012]; ©2012
• ISBN: 953-51-5226-2
• Descrizione fisica: 1 online resource (238 pages) : illustrations
• Disciplina: 617.481044
• Soggetti: Brain - Wounds and injuries
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di bibliografia: Includes bibliographical references.

Building value to last / / Crystal Maggelet ; with Sarah Ryther Francom and Laura Best Smith

• Record Nr.: UNINA9910793514703321
• Autore: Maggelet Crystal <1964->
• Pubbl/distr/stampa: Layton, Utah : , : Gibbs Smith, , [2019]; ©2019
• ISBN: 1-4236-4013-6
• Edizione: [1st ed.]
• Descrizione fisica: 1 online resource (192 pages)
• Disciplina: 338.76655092
• Soggetti: Truck stops - North America
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Prologue: a brief history of the Call Family -- My early years -- Soaring high: Flying J from 1980 to 2000 -- A new era -- Years of success -- Two risky acquisitions -- Sea of change -- Things fall apart -- Taking ; over as CEO.
• Sommario/riassunto: "The inspiring story of how Crystal Maggelet, the daughter of Flying J founder Jay Call, unexpectedly ended up as CEO of her father's company to help guide it back from the brink and on to even greater success--all during the throes of the Great Recession of the late 2000s."--Provided by the publisher.

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

• Record Nr.: UNINA9910484810403321
• 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. .