Learning With Uncertainty
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Learning with Uncertainty
Learning with uncertainty covers a broad range of scenarios in machine learning, this book mainly focuses on: (1) Decision tree learning with uncertainty, (2) Clustering under uncertainty environment, (3) Active learning based on uncertainty criterion, and (4) Ensemble learning in a framework of uncertainty. The book starts with the introduction to uncertainty including randomness, roughness, fuzziness and non-specificity and then comprehensively discusses a number of key issues in learning with uncertainty, such as uncertainty representation in learning, the influence of uncertainty on the performance of learning system, the heuristic design with uncertainty, etc. Most contents of the book are our research results in recent decades. The purpose of this book is to help the readers to understand the impact of uncertainty on learning processes. It comes with many examples to facilitate understanding. The book can be used as reference book or textbook for researcher fellows, senior undergraduates and postgraduates majored in computer science and technology, applied mathematics, automation, electrical engineering, etc.
The Management of Uncertainty
This investigative analysis studies why key European countries responded differently to the Chernobyl nuclear disaster, and what can be learned from it. The author details why the accident was defined differently in various countries, why actions were or were not taken, and what was learned about the management of nuclear risk. Furthermore, Liberatore studies the short-term and long-term responses and consequences of Chernobyl not only in specific countries, but within the European Union as a whole. Liberatore also provides a policy communication model to illustrate the interaction among the key personnel in such incidents: the scientists, the politicians, the interest groups, and the mass media. The author's focus upon uncertainty managementis a compelling account for all who seek to understand and improve the practical management of transboundary risks.
Uncertainty: A Catalyst for Creativity, Learning and Development
Author: Ronald A. Beghetto
language: en
Publisher: Springer Nature
Release Date: 2022-07-18
This edited volume brings together a group of international researchers and theorists from various intellectual and analytic traditions to explore the role uncertainty plays in creativity, learning, and development. Contributors to this volume draw on existing programs of research as well as introduce new and even speculative directions for research, theory and practice. Learning and life are filled with uncertainty. Although the experience of uncertainty can cause emotional discomfort or cognitive rigidity, uncertainty serves as a catalyst and condition for change. In this way, uncertainty represents a core facet in the interrelationship among creativity, learning, and development. Considerations for both the benefits and potential costs of uncertainty will be addressed in this volume with an aim of understanding how uncertainty can be better understood in light of creativity, learning, and development. Taken together this volume stands to contribute to our collective understanding of the role that uncertainty plays in learning and life and highlights how conceptualizing and studying uncertainty in new ways can promote positive and lasting change.