Reflections on the Foundations of Probability and Statistics: Essays in Honor of Teddy Seidenfeld: Theory and Decision Library A:, cartea 54
Editat de Thomas Augustin, Fabio Gagliardi Cozman, Gregory Wheeleren Limba Engleză Paperback – 15 ian 2024
Toate formatele și edițiile | Preț | Express |
---|---|---|
Paperback (1) | 717.38 lei 6-8 săpt. | |
Springer International Publishing – 15 ian 2024 | 717.38 lei 6-8 săpt. | |
Hardback (1) | 723.43 lei 6-8 săpt. | |
Springer International Publishing – 15 ian 2023 | 723.43 lei 6-8 săpt. |
Din seria Theory and Decision Library A:
- 18% Preț: 936.33 lei
- Preț: 376.16 lei
- 18% Preț: 942.08 lei
- 18% Preț: 933.22 lei
- 18% Preț: 1211.29 lei
- 15% Preț: 632.51 lei
- 18% Preț: 932.91 lei
- 15% Preț: 572.01 lei
- 15% Preț: 633.64 lei
- 15% Preț: 632.01 lei
- Preț: 383.18 lei
- 18% Preț: 931.68 lei
- 15% Preț: 630.41 lei
- Preț: 382.39 lei
- 15% Preț: 629.60 lei
- 18% Preț: 936.20 lei
- 15% Preț: 630.41 lei
- 18% Preț: 937.26 lei
- 18% Preț: 936.81 lei
- 18% Preț: 935.41 lei
- 15% Preț: 626.23 lei
- 18% Preț: 928.88 lei
- 15% Preț: 633.00 lei
- 18% Preț: 1360.41 lei
- 18% Preț: 1367.85 lei
- 20% Preț: 631.20 lei
- 15% Preț: 636.50 lei
Preț: 717.38 lei
Preț vechi: 874.85 lei
-18% Nou
Puncte Express: 1076
Preț estimativ în valută:
137.33€ • 141.24$ • 113.93£
137.33€ • 141.24$ • 113.93£
Carte tipărită la comandă
Livrare economică 18 februarie-04 martie
Preluare comenzi: 021 569.72.76
Specificații
ISBN-13: 9783031154386
ISBN-10: 303115438X
Pagini: 346
Ilustrații: XII, 346 p. 33 illus., 21 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.5 kg
Ediția:1st ed. 2022
Editura: Springer International Publishing
Colecția Springer
Seria Theory and Decision Library A:
Locul publicării:Cham, Switzerland
ISBN-10: 303115438X
Pagini: 346
Ilustrații: XII, 346 p. 33 illus., 21 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.5 kg
Ediția:1st ed. 2022
Editura: Springer International Publishing
Colecția Springer
Seria Theory and Decision Library A:
Locul publicării:Cham, Switzerland
Cuprins
An Interview with Teddy Seidenfeld.- The Value Provided by a Scientific Explanation.- A Gentle Approach to Imprecise Probability.- Foundations For Temporal Reasoning Using Lower Previsions Without A Possibility Space.- On the Equivalence of Normal and Extensive Form Representations of Games.- Dilation and Informativeness.- Playing with Sets of Lexicographic Probabilities and Sets of Desirable Gambles.- How to Assess Coherent Beliefs: A Comparison of Different Notions of Coherence in Dempster-Shafer Theory of Evidence.- Expected Utility in 3D.- On the Normative Status of Mixed Strategies.- On a Notion of Independence Proposed by Teddy Seidenfeld.- Coherent Choice Functions without Archimedeanity.- Quantifying Degrees of E-admissibility in Decision Making with Imprecise Probabilities.
Notă biografică
Thomas Augustin is Professor of Statistics at Ludwig-Maximilians-Universität München (LMU Munich), where he heads the "Foundations of Statistics and their Applications" Lab. His research interest is to develop set-valued methods for reliable statistical inference, decision making, and machine learning. For this, he utilizes
concepts from imprecise probabilities and partial identification to cope with different kinds of complex uncertainty, like non-randomly missing or coarsened data, non-standard measurement error, ambiguity,
conflicting information, and structural model indeterminacy.
Fabio G. Cozman is Professor of Computer Science at Escola Politécnica, Universidade de São Paulo (USP), Director of the Center for Artificial Intelligence at USP, with an interest in machine learning and knowledge/uncertainty representation. Engineer (USP) and PhD (Carnegie Mellon University, USA), he has served as Program and General Chair of the Conference on Uncertainty in Artificial Intelligence, Area Chair of the International Joint Conference on Artificial Intelligence, and Associate Editor of the Artificial Intelligence Journal, the Journal of Artificial Intelligence Research, and the Journal of Approximate Reasoning.
Gregory Wheeler is Professor of Philosophy and Computer Science at Frankfurt School of Finance & Management, where he heads the Center for Human & Machine Intelligence and is Academic Director of the Master of Applied Data Science program. His research interests concern the foundations of probability, bounded rationality, and decision-making under uncertainty involving underspecified models, conflicting information, computational resource bounds, and indeterminacy. He also co-founded Exaloan AG, a Frankfurt-based financial services software company, where he is Head of Machine Learning.
concepts from imprecise probabilities and partial identification to cope with different kinds of complex uncertainty, like non-randomly missing or coarsened data, non-standard measurement error, ambiguity,
conflicting information, and structural model indeterminacy.
Fabio G. Cozman is Professor of Computer Science at Escola Politécnica, Universidade de São Paulo (USP), Director of the Center for Artificial Intelligence at USP, with an interest in machine learning and knowledge/uncertainty representation. Engineer (USP) and PhD (Carnegie Mellon University, USA), he has served as Program and General Chair of the Conference on Uncertainty in Artificial Intelligence, Area Chair of the International Joint Conference on Artificial Intelligence, and Associate Editor of the Artificial Intelligence Journal, the Journal of Artificial Intelligence Research, and the Journal of Approximate Reasoning.
Gregory Wheeler is Professor of Philosophy and Computer Science at Frankfurt School of Finance & Management, where he heads the Center for Human & Machine Intelligence and is Academic Director of the Master of Applied Data Science program. His research interests concern the foundations of probability, bounded rationality, and decision-making under uncertainty involving underspecified models, conflicting information, computational resource bounds, and indeterminacy. He also co-founded Exaloan AG, a Frankfurt-based financial services software company, where he is Head of Machine Learning.
Textul de pe ultima copertă
This festschrift for Teddy Seidenfeld is a collection of newly commissioned essays on the foundations of probability and statistics by leading experts in the field. Each contribution touches on Teddy’s seminal contributions and gives an up-to-date state of the field that cannot be found elsewhere. The title, “a reflection on the foundations of probability and statistics”, which calls back to Teddy’s groundbreaking book (with Kadane and Schervish), “Rethinking the Foundations of Probability and Statistics”, bookends a career that has made fundamental contributions to a deeper understanding of uncertainty. It is aimed at all scholars engaged in probability and statistics.
Caracteristici
Brings together quality scholarship Examines findings in imprecise probability Contains unique state-of-the-art research