shinto (38 Ergebnisse)

Paperback. Zustand: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

Zustand: as new. Wie neu/Like new.

Zustand: New. pp. 43.

Paperback. Zustand: Brand New. 208 pages. 9.00x6.00x0.47 inches. In Stock.

Soft cover. Zustand: Good. vii, 82 pages : illustrations. Revised edition. Publisher's paper wrappers clean, sunning to front and to rear panels; contents as new. 210 grams.

Paperback. Zustand: Brand New. 120 pages. 9.00x6.00x0.28 inches. In Stock.

Paperback. Zustand: Brand New. 72 pages. 7.95x5.00x0.20 inches. In Stock.

Zustand: very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.

paperback. Zustand: Very Good. Cover and edges may have some wear.

Zustand: New. In.

Hardcover. Zustand: Brand New. 72 pages. 5.00x0.31x8.00 inches. In Stock.

1. Auflage 15 x 21 cm, 174 Seiten, kartoniert, 1 a Zustand ungelesen und neu.

Soft cover. Zustand: Fair. [x], 41, [42] pages. Bound in publisher's pictorial string-bound paper wrappers. Binding worn, upper fore-corner of front panel now lost (ca 3 sq. in.), small loss to head of spine, tear to head of spine, loss of ca 1.25 in. from foot of spine; contents bumped at upper fore-corner but unmarked. A flawed copy of an uncommon book. 150 grams.

Hardcover. Zustand: New. Language: English. The Title 'Outlines of the Mahayana as taught by Buddha written/authored/edited by Shinto Kuroda', published in the year 2013. The ISBN 9789333315333 is assigned to the Hardcover version of this title. This book has total of pp. 43 (Pages). The publisher of this title is Facsimile Publisher. This Book is in English. The subject of this book is History. Size of the book is 14.34 x 22.59 cms Vol: 43.

Zustand: AS NEW. Etat de NEUF / AS NEW condition 9782913413313 9782913413313 1007F 7.

Zustand: New. In.

Softcover. Octavo, 60 pages. In Fair condition only. Fukuro-toji binding with grey and pink printed paper wraps; blank spine. Thread torn; sewing beginning to loosen. Front wrap with small sticker bearing handwritten "25" to upper left corner. Insect damage, significant bumping to corners and edges, and light plus fading and staining to wraps. Text block lightly age toned with a few ink and pencil annotations; a printed paper slip with transliterated and translated title pasted to front free endpaper. Text in Chinese. SH Consignment. 1370456. Special Collections.

Paperback. Zustand: Good. 1958 paperback, Good to VG, moderate wear, yellowed pages, some creased corner tips and minor blemishes.

Taschenbuch. Zustand: Neu. Outlines of the Mahâyâna as Taught by Buddha | Shinto Kuroda (u. a.) | Taschenbuch | 44 S. | Englisch | 2017 | hansebooks | EAN 9783337246822 | Verantwortliche Person für die EU: Hansebooks GmbH, Trakehner Weg 52, 22844 Norderstedt, gb[at]hansebooks[dot]com | Anbieter: preigu.

Paperback. Zustand: Brand New. 1st edition. 59 pages. 9.25x6.25x0.50 inches. In Stock.

Buch. Zustand: Neu. The Holy Kojiki -- Including, the Yengishiki | English Transla Of the Shinto Religion | Buch | Gebunden | Englisch | 2007 | Cosimo Classics | EAN 9781944529611 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.

Buch. Zustand: Neu. Neuware - Also known as the ''Records of Ancient Matters,'' this is the ''official'' story of the Japanese peoples, first written down in the 8th century and documenting the creation of the world, the gods, and Japan. The oldest known document in the Japanese language, this is a vital text of the Shinto religion, a beautiful evocation of the mythology and traditions of ancient Japan. This edition also includes the Yengishiki, a compilation of Shinto rituals, including ''The Harvest Ritual,'' ''The Ritual for the Wind-Gods,'' ''The Ritual for EvilSpirits,'' and others.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book introduces the gamma-divergence, a measure of distance between probability distributions that was proposed by Fujisawa and Eguchi in 2008. The gamma-divergence has been extensively explored to provide robust estimation when the power index Gamma is positive. The gamma-divergence can be defined even when the power index Gamma is negative, as long as the condition of integrability is satisfied. Thus, the authors consider the gamma-divergence defined on a set of discrete distributions. The arithmetic, geometric, and harmonic means for the distribution ratios are closely connected with the gamma-divergence with a negative Gamma. In particular, the authors call the geometric-mean (GM) divergence the gamma-divergence when Gamma is equal to -1.The book begins by providing an overview of the gamma-divergence and its properties. It then goes on to discuss the applications of the gamma-divergence in various areas, including machine learning, statistics, and ecology. Bernoulli, categorical, Poisson, negative binomial, and Boltzmann distributions are discussed as typical examples. Furthermore, regression analysis models that explicitly or implicitly assume these distributions as the dependent variable in generalized linear models are discussed to apply the minimum gamma-divergence method.In ensemble learning, AdaBoost is derived by the exponential loss function in the weighted majority vote manner. It is pointed out that the exponential loss function is deeply connected to the GM divergence. In the Boltzmann machine, the maximum likelihood has to use approximation methods such as mean field approximation because of the intractable computation of the partition function. However, by considering the GM divergence and the exponential loss, it is shown that the calculation of the partition function is not necessary, and it can be executed without variational inference.

Zustand: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

Zustand: New. In.

Zustand: New. In.

Zustand: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This book explores minimum divergence methods of statistical machine learning for estimation, regression, prediction, and so forth, in which we engage in information geometry to elucidate their intrinsic properties of the corresponding loss functions, learning algorithms, and statistical models. One of the most elementary examples is Gauss's least squares estimator in a linear regression model, in which the estimator is given by minimization of the sum of squares between a response vector and a vector of the linear subspace hulled by explanatory vectors. This is extended to Fisher's maximum likelihood estimator (MLE) for an exponential model, in which the estimator is provided by minimization of the Kullback-Leibler (KL) divergence between a data distribution and a parametric distribution of the exponential model in an empirical analogue. Thus, we envisage a geometric interpretation of such minimization procedures such that a right triangle is kept with Pythagorean identity in the sense of the KL divergence. This understanding sublimates a dualistic interplay between a statistical estimation and model, which requires dual geodesic paths, called m-geodesic and e-geodesic paths, in a framework of information geometry. We extend such a dualistic structure of the MLE and exponential model to that of the minimum divergence estimator and the maximum entropy model, which is applied to robust statistics, maximum entropy, density estimation, principal component analysis, independent component analysis, regression analysis, manifold learning, boosting algorithm, clustering, dynamic treatment regimes, and so forth. We consider a variety of information divergence measures typically including KL divergence to express departure from one probability distribution to another. An information divergence is decomposed into the cross-entropy and the (diagonal) entropy in which the entropy associates with a generative model as a family of maximum entropy distributions; the cross entropy associates with a statistical estimation method via minimization of the empirical analogue based on given data. Thus any statistical divergence includes an intrinsic object between the generative model and the estimation method. Typically, KL divergence leads to the exponential model and the maximum likelihood estimation. It is shown that any information divergence leads to a Riemannian metric and a pair of the linear connections in the framework of information geometry. We focus on a class of information divergence generated by an increasing and convex function U, called U-divergence. It is shown that any generator function U generates the U-entropy and U-divergence, in which there is a dualistic structure between the U-divergence method and the maximum U-entropy model. We observe that a specific choice of U leads to a robust statistical procedurevia the minimum U-divergence method. If U is selected as an exponential function, then the corresponding U-entropy and U-divergence are reduced to the Boltzmann-Shanon entropy and the KL divergence; the minimum U-divergence estimator is equivalent to the MLE. For robust supervised learning to predict a class label we observe that the U-boosting algorithm performs well for contamination of mislabel examples if U is appropriately selected. We present such maximal U-entropy and minimum U-divergence methods, in particular, selecting a power function as U to provide flexible performance in statistical machine l.

Taschenbuch. Zustand: Neu. Legal Tech and the New Sharing Economy | Marcelo Corrales Compagnucci (u. a.) | Taschenbuch | Perspectives in Law, Business and Innovation | xvi | Englisch | 2021 | Springer | EAN 9789811513527 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Paperback. Zustand: Brand New. 276 pages. 9.25x6.10x0.65 inches. In Stock.

Hardcover. Zustand: Brand New. 225 pages. 9.25x6.25x0.75 inches. In Stock.