Download or read book Multiview Representation Learning for Political Science Research written by Etienne Gagnon and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "What is the best way to utilize social media data for political science research? Social media data is heterogenous in nature, meaning that it offers different types of information that are hard to analyze simulatenously. In this thesis, I propose multi-view representation learning, a machine learning framework that learns functions to jointly optimize different sets of vectors, as a technique to analyze heterogenous data. Multi-view learning has interesting potential applications to political science research. Applied research in Political Science typically focuses on one aspect of data. Multi-view learning makes it possible to combine information obtained from the different aspects of data to analyze an outcome. I apply multi-view learning to tweets produced by Canadian Members of Parliament to detect informal social links within the Liberal Party of Canada. The resulting representations correlate better with real-life parliamentary networks than other representation methods currently in use in the literature"--
Download or read book Multi view Representation Learning written by Pingjie Tang and published by . This book was released on 2020 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Towards General purpose Vision Via Multiview Contrastive Learning written by Yonglong Tian and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Representation learning plays a key role in building robust and general-purpose vision learners, and is a long-standing problem. It becomes increasingly interesting with the continuing explosion of data in our era. "However, most previous approaches are based on specific designs of strategies that are not generalizable. This thesis instead proposes and studies multiview contrastive learning, which is based on a simple mathematical principle -- discriminating between samples from the joint distribution and samples from the product of marginals. We firstly introduce the general framework of multiview contrastive learning (MCL). We demonstrate that this simple framework is able to deal with various representation learning problems, and often improves the state of the arts to the next level. Then we move forward by trying to understand the role of view selection in multiview contrastive learning from an information-theoretic point of view, and come up with an "InfoMin" principle, which connects to minimal sufficient statistics and information bottlenecks. Such principle is further demonstrated by supervised contrastive learning, which rivals or even beats the supervised cross-entropy learning on standard image classification benchmarks. In the last part, we extends multiview contrastive learning beyond standard problems or setups. We discuss a novel application of multiview contrastive learning, i.e., knowledge distillation, and present the first work that improves the efficiency of contrastive learning in open-ended uncurated scenarios.
Download or read book Multi view Robust Representation Learning written by Lusi Li and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Politics of Representation written by Heinz Eulau and published by SAGE Publications, Incorporated. This book was released on 1978-08 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Foundations of Intelligent Systems written by Michelangelo Ceci and published by Springer Nature. This book was released on 2022-09-26 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 26th International Symposium on Foundations of Intelligent Systems, ISMIS 2022, held in Cosenza, Italy, in October 2022. The 31 regular papers, 11 short papers and 4 industrial papers presented in this volume were carefully reviewed and selected from 71 submissions. They were organized in topical sections as follows: Social Media and Recommendation; Natural Language Processing; Explainability; Intelligent Systems; Classification and Clustering; Complex Data; Medical Applications; Industrial Applications.
Download or read book Multi view Representation Learning for Natural Language Processing Applications written by Nikolaos Papasarantopoulos and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Artificial Intelligence in Marketing written by K. Sudhir and published by Emerald Group Publishing. This book was released on 2023-03-13 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: Review of Marketing Research pushes the boundaries of marketing—broadening the marketing concept to make the world a better place. Here, leading scholars explore how marketing is currently shaping, and being shaped by, the evolution of Artificial Intelligence (AI).
Download or read book Dissertation Abstracts International written by and published by . This book was released on 1981 with total page 692 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Learning Representation for Multi View Data Analysis written by Zhengming Ding and published by Springer. This book was released on 2018-12-06 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book equips readers to handle complex multi-view data representation, centered around several major visual applications, sharing many tips and insights through a unified learning framework. This framework is able to model most existing multi-view learning and domain adaptation, enriching readers’ understanding from their similarity, and differences based on data organization and problem settings, as well as the research goal. A comprehensive review exhaustively provides the key recent research on multi-view data analysis, i.e., multi-view clustering, multi-view classification, zero-shot learning, and domain adaption. More practical challenges in multi-view data analysis are discussed including incomplete, unbalanced and large-scale multi-view learning. Learning Representation for Multi-View Data Analysis covers a wide range of applications in the research fields of big data, human-centered computing, pattern recognition, digital marketing, web mining, and computer vision.
Download or read book Comprehensive Dissertation Index written by and published by . This book was released on 1984 with total page 920 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Routledge Companion to Digital Journalism Studies written by Bob Franklin and published by Taylor & Francis. This book was released on 2016-11-18 with total page 641 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Routledge Companion to Digital Journalism Studies offers an unprecedented collection of essays addressing the key issues and debates shaping the field of Digital Journalism Studies today. Across the last decade, journalism has undergone many changes, which have driven scholars to reassess its most fundamental questions, and in the face of digital change, to ask again: ‘Who is a journalist?’ and ‘What is journalism?’. This companion explores a developing scholarly agenda committed to understanding digital journalism and brings together the work of key scholars seeking to address key theoretical concerns and solve unique methodological riddles. Compiled of 58 original essays from distinguished academics across the globe, this Companion draws together the work of those making sense of this fundamental reconceptualization of journalism, and assesses its impacts on journalism’s products, its practices, resources, and its relationship with audiences. It also outlines the challenge presented by studying digital journalism and, more importantly, offers a first set of answers. This collection is the very first of its kind to attempt to distinguish this emerging field as a unique area of academic inquiry. Through identifying its core questions and presenting its fundamental debates, this Companion sets the agenda for years to come in defining this new field of study as Digital Journalism Studies, making it an essential point of reference for students and scholars of journalism.
Download or read book Federated Learning written by Qiang Yang and published by Springer Nature. This book was released on 2020-11-25 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. It is timely as federated learning is becoming popular after the release of the General Data Protection Regulation (GDPR). Since federated learning aims to enable a machine model to be collaboratively trained without each party exposing private data to others. This setting adheres to regulatory requirements of data privacy protection such as GDPR. This book contains three main parts. Firstly, it introduces different privacy-preserving methods for protecting a federated learning model against different types of attacks such as data leakage and/or data poisoning. Secondly, the book presents incentive mechanisms which aim to encourage individuals to participate in the federated learning ecosystems. Last but not least, this book also describes how federated learning can be applied in industry and business to address data silo and privacy-preserving problems. The book is intended for readers from both the academia and the industry, who would like to learn about federated learning, practice its implementation, and apply it in their own business. Readers are expected to have some basic understanding of linear algebra, calculus, and neural network. Additionally, domain knowledge in FinTech and marketing would be helpful.”
Download or read book Resources in Education written by and published by . This book was released on 1995 with total page 1026 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Multiview written by D. E. Avison and published by Wiley-Blackwell. This book was released on 1990 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Optimization for Machine Learning written by Suvrit Sra and published by MIT Press. This book was released on 2012 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt: An up-to-date account of the interplay between optimization and machine learning, accessible to students and researchers in both communities. The interplay between optimization and machine learning is one of the most important developments in modern computational science. Optimization formulations and methods are proving to be vital in designing algorithms to extract essential knowledge from huge volumes of data. Machine learning, however, is not simply a consumer of optimization technology but a rapidly evolving field that is itself generating new optimization ideas. This book captures the state of the art of the interaction between optimization and machine learning in a way that is accessible to researchers in both fields. Optimization approaches have enjoyed prominence in machine learning because of their wide applicability and attractive theoretical properties. The increasing complexity, size, and variety of today's machine learning models call for the reassessment of existing assumptions. This book starts the process of reassessment. It describes the resurgence in novel contexts of established frameworks such as first-order methods, stochastic approximations, convex relaxations, interior-point methods, and proximal methods. It also devotes attention to newer themes such as regularized optimization, robust optimization, gradient and subgradient methods, splitting techniques, and second-order methods. Many of these techniques draw inspiration from other fields, including operations research, theoretical computer science, and subfields of optimization. The book will enrich the ongoing cross-fertilization between the machine learning community and these other fields, and within the broader optimization community.
Download or read book Allison Research Index of Art and Design written by and published by . This book was released on 1991 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt:
