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Cadê Clarisse?
Clarisse está aprendendo a engatinhar e sua curiosidade para conhecer o mundo é imensa. Com a pergunta que se repete a cada página, “Cadê Clarisse?”, a autora prende a atenção das crianças, junto com as cores vivas das ilustrações, feitas com massinha de modelar.
International Arbitration: Law and Practice
International Arbitration: Law and Practice (Third Edition) provides comprehensive and authoritative coverage of the basic principles and legal doctrines, and the practice, of international arbitration. The book contains a systematic, but concise, treatment of all aspects of the arbitral process, including international arbitration agreements, international arbitral proceedings and international arbitral awards. The Third Edition guides both students and practitioners through the entire arbitral process, beginning with drafting, enforcing and interpreting international arbitration agreements, to selecting arbitrators and conducting arbitral proceedings, to recognizing, enforcing and seeking ...
Machine Learning, Optimization, and Data Science
This two-volume set, LNCS 12565 and 12566, constitutes the refereed proceedings of the 6th International Conference on Machine Learning, Optimization, and Data Science, LOD 2020, held in Siena, Italy, in July 2020. The total of 116 full papers presented in this two-volume post-conference proceedings set was carefully reviewed and selected from 209 submissions. These research articles were written by leading scientists in the fields of machine learning, artificial intelligence, reinforcement learning, computational optimization, and data science presenting a substantial array of ideas, technologies, algorithms, methods, and applications.
Federated Learning
How is it possible to allow multiple data owners to collaboratively train and use a shared prediction model while keeping all the local training data private? Traditional machine learning approaches need to combine all data at one location, typically a data center, which may very well violate the laws on user privacy and data confidentiality. Today, many parts of the world demand that technology companies treat user data carefully according to user-privacy laws. The European Union's General Data Protection Regulation (GDPR) is a prime example. In this book, we describe how federated machine learning addresses this problem with novel solutions combining distributed machine learning, cryptography and security, and incentive mechanism design based on economic principles and game theory. We explain different types of privacy-preserving machine learning solutions and their technological backgrounds, and highlight some representative practical use cases. We show how federated learning can become the foundation of next-generation machine learning that caters to technological and societal needs for responsible AI development and application.
International Arbitration and the COVID-19 Revolution
International Arbitration and the COVID-19 Revolution Edited by Maxi Scherer, Niuscha Bassiri & Mohamed S. Abdel Wahab The impact of the COVID-19 pandemic on all major economic sectors and industries has triggered profound and systemic changes in international arbitration. Moreover, the fact that entire proceedings are now being conducted remotely constitutes so significant a deviation from the norm as to warrant the designation ‘revolution’. This timely book is the first to describe and analyse how the COVID-19 crisis has redefined arbitral practice, with critical appraisal from well-known practitioners of the pandemic’s effects on substantive and procedural aspects from the commencem...
