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Titlebook: Weimar and the Rise of Hitler; A. J. Nicholls Textbook 1991Latest edition Macmillan Publishers Limited 1991 Adolf Hitler.peace.revolution

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書目名稱Weimar and the Rise of Hitler
編輯A. J. Nicholls
視頻videohttp://file.papertrans.cn/1022/1021991/1021991.mp4
叢書名稱The Making of the Twentieth Century
圖書封面Titlebook: Weimar and the Rise of Hitler;  A. J. Nicholls Textbook 1991Latest edition Macmillan Publishers Limited 1991 Adolf Hitler.peace.revolution
描述In this extensively revised third edition, the book takes into account the large body of recent research on this controversial period. A completely new introduction describes how these developments in scholarship have affected our view of Weimar, and a new final chapter discusses the relationship between the economic and social tensions in Germany during this period and the rise of Hitler. Throughout the book the author has updated the text and added new material and references, and the already extensive bibliography has been substantially expanded.
出版日期Textbook 1991Latest edition
關(guān)鍵詞Adolf Hitler; peace; revolution
版次3
doihttps://doi.org/10.1007/978-1-349-21337-5
copyrightMacmillan Publishers Limited 1991
The information of publication is updating

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A. J. Nichollsc features, the model trained on the de-domained corpora can effectively learn common expression patterns in different domains. Subsequently, we adapt the learned domain-agnostic features to the target domain through domain adaptation training. We conduct experiments on Chinese dialogue datasets fro
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發(fā)表于 2025-3-22 14:36:26 | 只看該作者
A. J. Nichollsulti-Set Skeleton Prediction and outputs a univariate symbolic skeleton. Thus, such skeletons represent explanations of the function approximated by the regression NN. Experimental results demonstrate that this method learns skeleton expressions matching the underlying functions and outperforms two
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A. J. Nichollsation as Markov chains which enables our simulations to be carried out in poly-time. We then evaluate our proposed algorithm against various competitive and realistic baselines using a theme park dataset. Our simulation results highlight the existence of the Selfish Routing problem and show that SCA
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A. J. Nichollshe paper suggests two practically motivated smoothing heuristics to address common biases in observational data, a time-based smoothing to handle concept drift and a class-wise smoothing based on class priors to mitigate data imbalance. The effectiveness of the proposed methods is demonstrated on fo
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