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In light of the rapid rise of new trends and applications in various natural language processing tasks, this book presents high-quality research in the... Læs mere
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This Pivot reconsiders the controversial literary figure of Lin Shu and the debate surrounding his place in the history of Modern Chinese Literature.
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Deep reinforcement learning (DRL) is the combination of reinforcement learning (RL) and deep learning. The first part introduces the foundations of deep learning, reinforcement learning (RL) and widely used deep RL methods and discusses their implementation.
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The third part presents various work based on the probability principle, including dual supervised learning and dual inference based on the joint-probability principle and dual semi-supervised learning based on the marginal-probability principle.
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This textbook covers the concepts, theories, and implementations of text mining and natural language processing (NLP). In the five chapters of Part 2, all the core concepts of text... Læs mere
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The book focuses on model-based empirical methods where data annotations and model predictions are treated as training data for interpretable probabilistic models from the well-understood families of generalized additive models (GAMs) and linear mixed effects models (LMEMs).