Haullasi löytyi yhteensä 12 tuotetta Haluatko tarkentaa hakukriteerejä?
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Miroslav Karny Springer London Ltd (2005) Kovakantinen kirja 129,90 € |
Miroslav Karny (ed.) Springer (2014) Pehmeäkantinen kirja 129,90 € |
Kevin Warwick; Miroslav Karny Birkhauser Boston Inc (1997) Kovakantinen kirja 97,90 € |
Vera Kurkova (ed.); Nigel C. Steele (ed.); Roman Neruda (ed.); Miroslav Karny (ed.) Springer (2001) Pehmeäkantinen kirja 49,60 € |
Tatiana Valentine Guy; Miroslav Kárný; David H. Wolpert Springer-Verlag Berlin and Heidelberg GmbH & Co. KG (2011) Kovakantinen kirja 129,90 € |
Tatiana V Guy (ed.); Miroslav Karny (ed.); David Wolpert (ed.) Springer (2013) Kovakantinen kirja 97,90 € |
Kevin Warwick; Miroslav Karny Springer-Verlag New York Inc. (2012) Pehmeäkantinen kirja 97,90 € |
Kevin Warwick (ed.); Miroslav Karny (ed.); Alena Halouskova (ed.) Springer (1991) Pehmeäkantinen kirja 49,60 € |
Tatiana V. Guy; Miroslav Kárný; David H. Wolpert Springer International Publishing AG (2015) Kovakantinen kirja 97,90 € |
Tatiana V. Guy; Miroslav Kárný; David H. Wolpert Springer International Publishing AG (2016) Pehmeäkantinen kirja 97,90 € |
Tatiana V Guy (ed.); Miroslav Karny (ed.); David Wolpert (ed.) Springer (2015) Pehmeäkantinen kirja 97,90 € |
Tatiana Valentine Guy (ed.); Miroslav Kárný (ed.); David H. Wolpert (ed.) Springer (2016) Pehmeäkantinen kirja 129,90 € |
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Optimized Bayesian Dynamic Advising - Theory and Algorithms This work summarizes the theoretical and algorithmic basis of optimized pr- abilistic advising. It developed from a series of targeted research projects s- ported both by the European Commission and Czech grant bodies. The source text has served as a common basis of communication for the research team. When accumulating and re?ning the material we found that the text could also serve as • a grand example of the strength of dynamic Bayesian decision making, • a practical demonstration that computational aspects do matter, • a reference to ready particular solutions in learning and optimization of decision-making strategies, • a source of open and challenging problems for postgraduate students, young as well as experienced researchers, • a departure point for a further systematic development of advanced op- mized advisory systems, for instance, in multiple participant setting. These observations have inspired us to prepare this book. Prague, Czech Republic Miroslav K´ arn´ y October 2004 Josef B¨ ohm Tatiana V. Guy Ladislav Jirsa Ivan Nagy Petr Nedoma Ludv´ ?k Tesa? r Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1. 1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1. 2 State of the art . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1. 2. 1 Operator supports . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1. 2. 2 Mainstream multivariate techniques . . . . . . . . . . . . . . . . . 4 1. 2. 3 Probabilistic dynamic optimized decision-making . . . . . . 6 1. 3 Developed advising and its role in computer support . . . . . . . . . 6 1. 4 Presentation style, readership andlayout . . . . . . . . . . . . . . . . . . . 7 1. 5 Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2 Underlying theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2. 1 General conventions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2. 2 Basic notions and notations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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