This book provides an international perspective of current work aimed at both clarifying the theoretical foundations for the use of multimodal representations as a part of effective science education pedagogy and the pragmatic application ...
This self-contained, comprehensive reference text describes the standard algorithms and demonstrates how these are used in different transfer learning paradigms.
This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP).
... learning of the teacher model. We also propose a local topology-aware distillation loss to transfer the local graph knowledge from the teacher to the student. We further propose a global topology loss to optimize the learning of the ...
This book gives a clear understanding of the principles and methods of neural network and deep learning concepts, showing how the algorithms that integrate deep learning as a core component are applied to medical image detection, ...
Only about 30 percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. These proceedings contain all of the papers that were presented at the 2000 conference.
This book takes a radically different look at communication, and in doing so presents a series of challenges to accepted views on language, on communication, on teaching and, above all, on learning.
This book provides a comprehensive and self-contained introduction to federated learning, ranging from the basic knowledge and theories to various key applications. Privacy and incentive issues are the focus of this book.