Lifelong And Continual Learning Dialogue Systems
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Lifelong And Continual Learning Dialogue Systems
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Author : Sahisnu Mazumder
language : en
Publisher: Springer Nature
Release Date : 2024-01-08
Lifelong And Continual Learning Dialogue Systems written by Sahisnu Mazumder and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-08 with Computers categories.
This book introduces the new paradigm of lifelong and continual learning dialogue systems to endow dialogue systems with the ability to learn continually by themselves through their own self-initiated interactions with their users and the working environments. The authors present the latest developments and techniques for building such continual learning dialogue systems. The book explains how these developments allow systems to continuously learn new language expressions, lexical and factual knowledge, and conversational skills through interactions and dialogues. Additionally, the book covers techniques to acquire new training examples for learning new tasks during the conversation. The book also reviews existing work on lifelong learning and discusses areas for future research.
Lifelong Machine Learning
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Author : Zhiyuan Chen
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2018-08-14
Lifelong Machine Learning written by Zhiyuan Chen and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-14 with Computers categories.
Lifelong Machine Learning, Second Edition is an introduction to an advanced machine learning paradigm that continuously learns by accumulating past knowledge that it then uses in future learning and problem solving. In contrast, the current dominant machine learning paradigm learns in isolation: given a training dataset, it runs a machine learning algorithm on the dataset to produce a model that is then used in its intended application. It makes no attempt to retain the learned knowledge and use it in subsequent learning. Unlike this isolated system, humans learn effectively with only a few examples precisely because our learning is very knowledge-driven: the knowledge learned in the past helps us learn new things with little data or effort. Lifelong learning aims to emulate this capability, because without it, an AI system cannot be considered truly intelligent. Research in lifelong learning has developed significantly in the relatively short time since the first edition of this book was published. The purpose of this second edition is to expand the definition of lifelong learning, update the content of several chapters, and add a new chapter about continual learning in deep neural networks—which has been actively researched over the past two or three years. A few chapters have also been reorganized to make each of them more coherent for the reader. Moreover, the authors want to propose a unified framework for the research area. Currently, there are several research topics in machine learning that are closely related to lifelong learning—most notably, multi-task learning, transfer learning, and meta-learning—because they also employ the idea of knowledge sharing and transfer. This book brings all these topics under one roof and discusses their similarities and differences. Its goal is to introduce this emerging machine learning paradigm and present a comprehensive survey and review of the important research results and latest ideas in the area. This book is thus suitable for students, researchers, and practitioners who are interested in machine learning, data mining, natural language processing, or pattern recognition. Lecturers can readily use the book for courses in any of these related fields.
Natural Language Understanding In Conversational Ai With Deep Learning
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Author : Soyeon Caren Han
language : en
Publisher: Springer Nature
Release Date : 2025-01-11
Natural Language Understanding In Conversational Ai With Deep Learning written by Soyeon Caren Han and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-11 with Computers categories.
This book provides a comprehensive introduction to conversational spoken language understanding and surveys recent advances in conversational AI. It guides the reader through the history, current advancements, and future of natural language understanding (NLU) in human-computer interactions. To this end, the book is structured in seven chapters: Introduction to Natural Language Understanding lays the foundation by tracing the evolution of NLU from early human communication to modern human-computer interactions. Prerequisites and Glossary for Natural Language Understanding then serves as a foundational resource, consolidating essential prerequisites and key terminologies relevant across the book. Single-Turn Natural Language Understanding looks at Single-Turn NLU, focusing on tasks that involve interpreting and processing user inputs in a single interaction, while Multi-Turn Natural Language Understanding moves on systems for extended interactions with users and explores techniques for managing dialogues, using context and integrating external knowledge bases. Next, Evaluating Natural Language Understanding discusses the annotation of datasets and various performance assessment methods, covering different levels of understanding from intent recognition to slot filling and domain classification. Applications and Case Studies in Natural Language Understanding subsequently shows real-world applications of NLU in finance, medicine, and law. Eventually Challenges, Conclusions and Future Directions explores the core obstacles hindering the advancement of NLU, including ambiguity, domain adaptation, data scarcity, and ethical concerns. By understanding these challenges, this chapter highlights the ongoing work needed to advance NLU. This book mainly targets researchers, PhD students, and professionals who are entering this field and look for a state-of-the-art introduction to NLU applied in conversational systems such as chatbots, large language models, or educational systems.
Database Systems For Advanced Applications
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Author : Xin Wang
language : en
Publisher: Springer Nature
Release Date : 2023-04-13
Database Systems For Advanced Applications written by Xin Wang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-13 with Computers categories.
The four-volume set LNCS 13943, 13944, 13945 and 13946 constitutes the proceedings of the 28th International Conference on Database Systems for Advanced Applications, DASFAA 2023, held in April 2023 in Tianjin, China. The total of 125 full papers, along with 66 short papers, are presented together in this four-volume set was carefully reviewed and selected from 652 submissions. Additionally, 15 industrial papers, 15 demo papers and 4 PhD consortium papers are included. The conference presents papers on subjects such as model, graph, learning, performance, knowledge, time, recommendation, representation, attention, prediction, and network.
Database Systems For Advanced Applications
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Author : Makoto Onizuka
language : en
Publisher: Springer Nature
Release Date : 2024-12-12
Database Systems For Advanced Applications written by Makoto Onizuka and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-12 with Mathematics categories.
The seven-volume set LNCS 14850-14856 constitutes the proceedings of the 29th International Conference on Database Systems for Advanced Applications, DASFAA 2024, held in Gifu, Japan, in July 2024. The total of 147 full papers, along with 85 short papers, presented together in this seven-volume set was carefully reviewed and selected from 722 submissions. Additionally, 14 industrial papers, 18 demo papers and 6 tutorials are included. The conference presents papers on subjects such as: Part I: Spatial and temporal data; database core technology; federated learning. Part II: Machine learning; text processing. Part III: Recommendation; multi-media. Part IV: Privacy and security; knowledge base and graphs. Part V: Natural language processing; large language model; time series and stream data. Part VI: Graph and network; hardware acceleration. Part VII: Emerging application; industry papers; demo papers.
Pervasive Computing Technologies For Healthcare
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Author : Athanasios Tsanas
language : en
Publisher: Springer Nature
Release Date : 2023-06-10
Pervasive Computing Technologies For Healthcare written by Athanasios Tsanas and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-10 with Medical categories.
This book constitutes the refereed proceedings of the 16th EAI International Conference on Pervasive Computing Technologies for Healthcare, PervasiveHealth 2022, which took place in Thessaloniki, Greece, in December 2022. The 45 full papers included in this volume were carefully reviewed and selected from 120 submissions. The papers are organized in the following topical sections: personal informatics and wearable devices; computer vision; IoT-HR: Internet of things in health research; pervasive health for COVID-19; machine learning, human activity recognition and speech recognition; software frameworks and interoperability; facial recognition, gesture recognition and object detection; machine learning, predictive models and personalised healthcare; human-centred design of pervasive health solutions; personalized healthcare.
Increasing Naturalness And Flexibility In Spoken Dialogue Interaction
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Author : Erik Marchi
language : en
Publisher: Springer Nature
Release Date : 2021-03-10
Increasing Naturalness And Flexibility In Spoken Dialogue Interaction written by Erik Marchi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-10 with Technology & Engineering categories.
This book compiles and presents a synopsis on current global research efforts to push forward the state of the art in dialogue technologies, including advances to language and context understanding, and dialogue management, as well as human–robot interaction, conversational agents, question answering and lifelong learning for dialogue systems.
Machine Learning And Knowledge Discovery In Databases Research Track
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Author : Albert Bifet
language : en
Publisher: Springer Nature
Release Date : 2024-08-29
Machine Learning And Knowledge Discovery In Databases Research Track written by Albert Bifet and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-29 with Computers categories.
This multi-volume set, LNAI 14941 to LNAI 14950, constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2024, held in Vilnius, Lithuania, in September 2024. The papers presented in these proceedings are from the following three conference tracks: - Research Track: The 202 full papers presented here, from this track, were carefully reviewed and selected from 826 submissions. These papers are present in the following volumes: Part I, II, III, IV, V, VI, VII, VIII. Demo Track: The 14 papers presented here, from this track, were selected from 30 submissions. These papers are present in the following volume: Part VIII. Applied Data Science Track: The 56 full papers presented here, from this track, were carefully reviewed and selected from 224 submissions. These papers are present in the following volumes: Part IX and Part X.
Text Speech And Dialogue
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Author : Elmar Nöth
language : en
Publisher: Springer Nature
Release Date : 2024-08-31
Text Speech And Dialogue written by Elmar Nöth and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-31 with Computers categories.
The two-volume set LNAI 15048 and 15049 constitutes the refereed proceedings of the 27th International Conference on Text, Speech, and Dialogue, TSD 2024, held in Brno, Czech Republic, during September 9–13, 2024. The 50 revised full papers presented in these deadline proceedings were carefully reviewed and selected from 103 submissions. The papers are organized in the following topical sections: Part I: Text Part II: Speech, Dialogue
Data Centric Artificial Intelligence For Multidisciplinary Applications
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Author : Parikshit N Mahalle
language : en
Publisher: CRC Press
Release Date : 2024-06-06
Data Centric Artificial Intelligence For Multidisciplinary Applications written by Parikshit N Mahalle and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-06 with Computers categories.
This book explores the need for a data‐centric AI approach and its application in the multidisciplinary domain, compared to a model‐centric approach. It examines the methodologies for data‐centric approaches, the use of data‐centric approaches in different domains, the need for edge AI and how it differs from cloud‐based AI. It discusses the new category of AI technology, "data‐centric AI" (DCAI), which focuses on comprehending, utilizing, and reaching conclusions from data. By adding machine learning and big data analytics tools, data‐centric AI modifies this by enabling it to learn from data rather than depending on algorithms. It can therefore make wiser choices and deliver more precise outcomes. Additionally, it has the potential to be significantly more scalable than conventional AI methods. • Includes a collection of case studies with experimentation results to adhere to the practical approaches • Examines challenges in dataset generation, synthetic datasets, analysis, and prediction algorithms in stochastic ways • Discusses methodologies to achieve accurate results by improving the quality of data • Comprises cases in healthcare and agriculture with implementation and impact of quality data in building AI applications