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Record Nr. |
UNINA9910783362203321 |
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Autore |
Taruskin Richard |
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Titolo |
Text and act [[electronic resource] ] : essays on music and performance / / Richard Taruskin |
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Pubbl/distr/stampa |
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New York, : Oxford University Press, 1995 |
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ISBN |
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0-19-772928-2 |
1-280-45099-1 |
0-19-535743-4 |
1-60256-031-5 |
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Descrizione fisica |
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1 online resource (391 p.) |
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Disciplina |
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Soggetti |
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Performance practice (Music) |
Style, Musical |
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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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Description based upon print version of record. |
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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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Contents; Author's Note; INTRODUCTION; Last Thoughts First; IN THEORY; 1. On Letting the Music Speak for Itself; 2. The Limits of Authenticity: A Contribution; 3. Down with the Fence; 4. The Pastness of the Present and the Presence of the Past; 5. What-or Where-Is the Original?; 6. The Modern Sound of Early Music; 7. Tradition and Authority; IN PRACTICE; Beethoven; 8. The New Antiquity; 9. Resisting the Ninth; Mozart; 10. An Icon for Our Time; 11. A Mozart Wholly Ours; 12. Old (New) Instruments, New (Old) Tempos; Bach; 13. Backslide or Harbinger?; 14. Facing up, Finally, to Bach's Dark Vision |
15. The Crooked Straight and the Rough Places PlainAntiquarian Innocence; 16. Report from Lincoln Center: The International Josquin Festival-Conference, 21-25 June 1971; 17. The Price of Literacy, or, Why We Need Musicology; 18. High, Sweet, and Loud; 19. Text and Act; Full Circle; 20. Stravinsky Lite (Even ""The Rite""); Index; A; B; C; D; E; F; G; H; I; J; K; L; M; N; O; P; Q; R; S; T; U; V; W; X; Y; Z |
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Sommario/riassunto |
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Over the last dozen years, the writings of Richard Taruskin have transformed the debate about ""early music"" and ""authenticity."" Text and Act collects for the first time the most important of Taruskin's |
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essays and reviews from this period, many of which now classics in the field. Taking a wide-ranging cultural view of the phenomenon, he shows that the movement, far from reviving ancient traditions, in fact represents the only truly modern style of performance being offered today. He goes on to contend that the movement is therefore far more valuable and even authentic than the historical ve |
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2. |
Record Nr. |
UNINA9910299849303321 |
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Titolo |
Partitional Clustering Algorithms / / edited by M. Emre Celebi |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
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ISBN |
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Edizione |
[1st ed. 2015.] |
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Descrizione fisica |
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1 online resource (420 p.) |
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Disciplina |
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Soggetti |
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Electrical engineering |
Computers |
Signal processing |
Image processing |
Speech processing systems |
Communications Engineering, Networks |
Information Systems and Communication Service |
Signal, Image and Speech Processing |
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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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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references at the end of each chapters. |
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Nota di contenuto |
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Recent developments in model-based clustering with applications -- Accelerating Lloyd’s algorithm for k-means clustering -- Linear, Deterministic, and Order-Invariant Initialization Methods for the K-Means Clustering Algorithm -- Nonsmooth optimization based algorithms in cluster analysis -- Fuzzy Clustering Algorithms and Validity Indices for Distributed Data -- Density Based Clustering: |
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Alternatives to DBSCAN -- Nonnegative matrix factorization for interactive topic modeling and document clustering -- Overview of overlapping partitional clustering methods -- On Semi-Supervised Clustering -- Consensus of Clusterings based on High-order Dissimilarities -- Hubness-Based Clustering of High-Dimensional Data -- Clustering for Monitoring Distributed Data Streams. |
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Sommario/riassunto |
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This book summarizes the state-of-the-art in partitional clustering. Clustering, the unsupervised classification of patterns into groups, is one of the most important tasks in exploratory data analysis. Primary goals of clustering include gaining insight into, classifying, and compressing data. Clustering has a long and rich history that spans a variety of scientific disciplines including anthropology, biology, medicine, psychology, statistics, mathematics, engineering, and computer science. As a result, numerous clustering algorithms have been proposed since the early 1950s. Among these algorithms, partitional (nonhierarchical) ones have found many applications, especially in engineering and computer science. This book provides coverage of consensus clustering, constrained clustering, large scale and/or high dimensional clustering, cluster validity, cluster visualization, and applications of clustering. Examines clustering as it applies to large and/or high-dimensional data sets commonly encountered in realistic applications; Discusses algorithms specifically designed for partitional clustering; Covers center-based, competitive learning, density-based, fuzzy, graph-based, grid-based, metaheuristic, and model-based approaches. |
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