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Record Nr. |
UNINA9910790082703321 |
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Autore |
Storm William <1949-> |
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Titolo |
Irony and the modern theatre / / William Storm [[electronic resource]] |
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Pubbl/distr/stampa |
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Cambridge : , : Cambridge University Press, , 2011 |
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ISBN |
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1-139-06406-1 |
1-107-22183-8 |
1-283-11285-X |
9786613112859 |
1-139-07654-X |
1-139-08336-8 |
1-139-08109-8 |
1-139-07882-8 |
0-511-97483-3 |
1-139-07082-7 |
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Descrizione fisica |
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1 online resource (x, 256 pages) : digital, PDF file(s) |
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Collana |
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Cambridge studies in modern theatre |
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Classificazione |
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Disciplina |
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Soggetti |
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Irony in literature |
Drama - History and criticism |
Drama - Psychological aspects |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Title from publisher's bibliographic system (viewed on 05 Oct 2015). |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Introduction -- 1. Irony personified: Ibsen and The Master Builder -- 2. The character of irony in Chekhov -- 3. Irony and dialectic: Shaw's Candida -- 4. Pirandello's 'father' -- and Brecht's 'mother' -- 5. Absurdist irony: Ionesco's 'anti-play' -- 6. 'Ironist first-class': Stoppard's Arcadia -- 7. American ironies: Wasserstein and Kushner -- 8. Irony's theatre. |
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Sommario/riassunto |
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Irony and theatre share intimate kinships, not only regarding dramatic conflict, dialectic or wittiness, but also scenic structure and the verbal or situational ironies that typically mark theatrical speech and action. Yet irony today, in aesthetic, literary and philosophical contexts especially, is often regarded with skepticism - as ungraspable, or elusive to the point of confounding. Countering this tendency, Storm |
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advocates a wide-angle view of this master trope, exploring the ironic in major works by playwrights including Chekhov, Pirandello and Brecht, and in notable relation to well-known representative characters in drama from Ibsen's Halvard Solness to Stoppard's Septimus Hodge and Wasserstein's Heidi Holland. To the degree that irony is existential, its presence in the theatre relates directly to the circumstances and the expressiveness of the characters on stage. This study investigates how these key figures enact, embody, represent and personify the ironic in myriad situations in the modern and contemporary theatre. |
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2. |
Record Nr. |
UNINA9910896179403321 |
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Titolo |
Advanced Techniques in Optimization for Machine Learning and Imaging / / edited by Alessandro Benfenati, Federica Porta, Tatiana Alessandra Bubba, Marco Viola |
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Pubbl/distr/stampa |
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Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
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ISBN |
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Edizione |
[1st ed. 2024.] |
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Descrizione fisica |
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1 online resource (173 pages) |
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Collana |
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Springer INdAM Series, , 2281-5198 ; ; 61 |
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Disciplina |
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Soggetti |
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Machine learning |
Mathematical optimization |
Mathematical analysis |
Machine Learning |
Optimization |
Analysis |
Aprenentatge automàtic |
Optimització matemàtica |
Teories no lineals |
Processament digital d'imatges |
Llibres electrònics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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1.STEMPO dynamic Xray tomography phantom -- 2.On a fixed point continuation method for a convex optimization problem -- 3.Majoration Minimization for Sparse SVMs -- 4.Bilevel learning of regularization models and their discretization for image deblurring and super resolution -- 5.Non Log Concave and Nonsmooth Sampling via Langevin Monte Carlo Algorithms -- 6.On the inexact proximal Gauss-Newton methods for regularized nonlinear least squares problems. |
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Sommario/riassunto |
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In recent years, non-linear optimization has had a crucial role in the development of modern techniques at the interface of machine learning and imaging. The present book is a collection of recent contributions in the field of optimization, either revisiting consolidated ideas to provide formal theoretical guarantees or providing comparative numerical studies for challenging inverse problems in imaging. The work of these papers originated in the INdAM Workshop “Advanced Techniques in Optimization for Machine learning and Imaging” held in Roma, Italy, on June 20-24, 2022. The covered topics include non-smooth optimisation techniques for model-driven variational regularization, fixed-point continuation algorithms and their theoretical analysis for selection strategies of the regularization parameter for linear inverse problems in imaging, different perspectives on Support Vector Machines trained via Majorization-Minimization methods, generalization of Bayesian statistical frameworks to imaging problems, and creation of benchmark datasets for testing new methods and algorithms. |
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