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  • Robust Explainable AI

    Series series Artificial Intelligence (R0)
    The area of Explainable Artificial Intelligence (XAI) is concerned with providing methods and tools to improve the interpretability of black-box learning models. While several approaches exist to generate explanations, they are often lacking robustness, e.g., they may produce completely different explanations for similar events. This phenomenon has troubling implications, as lack of robustness ... Leer más

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    Machine Learning: A Constraint-Based Approach provides readers with a refreshing look at the basic models and algorithms of machine learning, with an emphasis on current topics of interest that includes neural networks and kernel machines. The book presents the information in a truly unified manner that is based on the notion of learning from environmental constraints. While regarding symbolic ... Leer más

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  • Graph Structures for Knowledge Representation and Reasoning

    6th International Workshop, GKR 2020, Virtual Event, September 5, 2020, Revised Selected Papers

    Series series Springer Nature Proceedings Computer Science
    This open access book constitutes the thoroughly refereed post-conference proceedings of the 6th International Workshop on Graph Structures for Knowledge Representation and Reasoning, GKR 2020, held virtually in September 2020, associated with ECAI 2020, the 24th European Conference on Artificial Intelligence.The 7 revised full papers presented together with 2 invited contributions were reviewed ... Leer más

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  • Neural Network Methods in Natural Language Processing

    Series series Synthesis Lectures on Human Language Technologies
    Neural networks are a family of powerful machine learning models and this book focuses on their application to natural language data.The first half of the book (Parts I and II) covers the basics of supervised machine learning and feed-forward neural networks, the basics of working with machine learning over language data, and the use of vector-based rather than symbolic representations for words. ... Leer más

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  • Deep Neural Networks and Data for Automated Driving

    Robustness, Uncertainty Quantification, and Insights Towards Safety

    This open access book brings together the latest developments from industry and research on automated driving and artificial intelligence.Environment perception for highly automated driving heavily employs deep neural networks, facing many challenges. How much data do we need for training and testing? How to use synthetic data to save labeling costs for training? How do we increase robustness and ... Leer más

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  • Representation Learning for Natural Language Processing

    Series series Computer Science (R0)
    This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those ... Leer más

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  • Generative Deep Learning with Python

    Unleashing the Creative Power of AI by Mastering AI and Python

    Dive into the world of Generative Deep Learning with Python, mastering GANs, VAEs, & autoregressive models through projects & advanced topics. Gain practical skills & theoretical knowledge to create groundbreaking AI applications.Key FeaturesComprehensive coverage of deep learning and generative models.In-depth exploration of GANs, VAEs, & autoregressive models & advanced topics in generative AI ... Leer más

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  • Introduction to Online Convex Optimization, second edition

    de Elad Hazan ...
    Series series Adaptive Computation and Machine Learning series
    New edition of a graduate-level textbook on that focuses on online convex optimization, a machine learning framework that views optimization as a process.In many practical applications, the environment is so complex that it is not feasible to lay out a comprehensive theoretical model and use classical algorithmic theory and/or mathematical optimization. Introduction to Online Convex Optimization ... Leer más

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  • Multi-Agent Reinforcement Learning

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  • Advances in Intelligent Data Analysis XVIII

    18th International Symposium on Intelligent Data Analysis, IDA 2020, Konstanz, Germany, April 27–29, 2020, Proceedings

    Series series Springer Nature Proceedings Computer Science
    This open access book constitutes the proceedings of the 18th International Conference on Intelligent Data Analysis, IDA 2020, held in Konstanz, Germany, in April 2020.The 45 full papers presented in this volume were carefully reviewed and selected from 114 submissions. Advancing Intelligent Data Analysis requires novel, potentially game-changing ideas. IDA’s mission is to promote ideas over ... Leer más

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  • Explainable AI with Python

    Series series Computer Science (R0)
    This book provides a full presentation of the current concepts and available techniques to make “machine learning” systems more explainable. The approaches presented can be applied to almost all the current “machine learning” models: linear and logistic regression, deep learning neural networks, natural language processing and image recognition, among the others.Progress in Machine Learning is ... Leer más

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  • Foundations of Semantic Communication Networks

    Comprehensive overview of the principles, theories, and techniques needed to build end-to-end semantic communication systems, with case studies included.In this rapidly evolving landscape, the integration of connected intelligence applications highlights the pressing need for networks to gain intelligence in a non-siloed and ad hoc manner. The traditional incremental approach to network design is ... Leer más

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