[PDF] An Algorithmic Perspective On Imitation Learning - eBooks Review

An Algorithmic Perspective On Imitation Learning


An Algorithmic Perspective On Imitation Learning
DOWNLOAD

Download An Algorithmic Perspective On Imitation Learning PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get An Algorithmic Perspective On Imitation Learning book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page



An Algorithmic Perspective On Imitation Learning


An Algorithmic Perspective On Imitation Learning
DOWNLOAD
Author : Takayuki Osa
language : en
Publisher:
Release Date : 2018

An Algorithmic Perspective On Imitation Learning written by Takayuki Osa and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Algorithms categories.


As robots and other intelligent agents move from simple environments and problems to more complex, unstructured settings, manually programming their behavior has become increasingly challenging and expensive. Often, it is easier for a teacher to demonstrate a desired behavior rather than attempt to manually engineer it. This process of learning from demonstrations, and the study of algorithms to do so, is called imitation learning. This work provides an introduction to imitation learning. It covers the underlying assumptions, approaches, and how they relate; the rich set of algorithms developed to tackle the problem; and advice on effective tools and implementation. We intend this paper to serve two audiences. First, we want to familiarize machine learning experts with the challenges of imitation learning, particularly those arising in robotics, and the interesting theoretical and practical distinctions between it and more familiar frameworks like statistical supervised learning theory and reinforcement learning. Second, we want to give roboticists and experts in applied artificial intelligence a broader appreciation for the frameworks and tools available for imitation learning. We pay particular attention to the intimate connection between imitation learning approaches and those of structured prediction Daum©♭ III et al. [2009].



Computer Vision Eccv 2022


Computer Vision Eccv 2022
DOWNLOAD
Author : Shai Avidan
language : en
Publisher: Springer Nature
Release Date : 2022-10-22

Computer Vision Eccv 2022 written by Shai Avidan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-22 with Computers categories.


The 39-volume set, comprising the LNCS books 13661 until 13699, constitutes the refereed proceedings of the 17th European Conference on Computer Vision, ECCV 2022, held in Tel Aviv, Israel, during October 23–27, 2022. The 1645 papers presented in these proceedings were carefully reviewed and selected from a total of 5804 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.



Understanding Machine Learning


Understanding Machine Learning
DOWNLOAD
Author : Shai Shalev-Shwartz
language : en
Publisher: Cambridge University Press
Release Date : 2014-05-19

Understanding Machine Learning written by Shai Shalev-Shwartz and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-19 with Computers categories.


Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage.



Algorithmic Foundations Of Robotics Xiii


Algorithmic Foundations Of Robotics Xiii
DOWNLOAD
Author : Marco Morales
language : en
Publisher: Springer Nature
Release Date : 2020-05-07

Algorithmic Foundations Of Robotics Xiii written by Marco Morales and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-07 with Technology & Engineering categories.


This book gathers the outcomes of the thirteenth Workshop on the Algorithmic Foundations of Robotics (WAFR), the premier event for showcasing cutting-edge research on algorithmic robotics. The latest WAFR, held at Universidad Politécnica de Yucatán in Mérida, México on December 9–11, 2018, continued this tradition. This book contains fifty-four papers presented at WAFR, which highlight the latest research on fundamental algorithmic robotics (e.g., planning, learning, navigation, control, manipulation, optimality, completeness, and complexity) demonstrated through several applications involving multi-robot systems, perception, and contact manipulation. Addressing a diverse range of topics in papers prepared by expert contributors, the book reflects the state of the art and outlines future directions in the field of algorithmic robotics.



Reinforcement Learning Methods In Speech And Language Technology


Reinforcement Learning Methods In Speech And Language Technology
DOWNLOAD
Author : Baihan Lin
language : en
Publisher: Springer Nature
Release Date : 2024-11-11

Reinforcement Learning Methods In Speech And Language Technology written by Baihan Lin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-11 with Technology & Engineering categories.


This book offers a comprehensive guide to reinforcement learning (RL) and bandits methods, specifically tailored for advancements in speech and language technology. Starting with a foundational overview of RL and bandit methods, the book dives into their practical applications across a wide array of speech and language tasks. Readers will gain insights into how these methods shape solutions in automatic speech recognition (ASR), speaker recognition, diarization, spoken and natural language understanding (SLU/NLU), text-to-speech (TTS) synthesis, natural language generation (NLG), and conversational recommendation systems (CRS). Further, the book delves into cutting-edge developments in large language models (LLMs) and discusses the latest strategies in RL, highlighting the emerging fields of multi-agent systems and transfer learning. Emphasizing real-world applications, the book provides clear, step-by-step guidance on employing RL and bandit methods to address challenges in speech and language technology. It includes case studies and practical tips that equip readers to apply these methods to their own projects. As a timely and crucial resource, this book is ideal for speech and language researchers, engineers, students, and practitioners eager to enhance the performance of speech and language systems and to innovate with new interactive learning paradigms from an interface design perspective.



Machine Learning In Finance


Machine Learning In Finance
DOWNLOAD
Author : Matthew F. Dixon
language : en
Publisher: Springer Nature
Release Date : 2020-07-01

Machine Learning In Finance written by Matthew F. Dixon and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-01 with Business & Economics categories.


This book introduces machine learning methods in finance. It presents a unified treatment of machine learning and various statistical and computational disciplines in quantitative finance, such as financial econometrics and discrete time stochastic control, with an emphasis on how theory and hypothesis tests inform the choice of algorithm for financial data modeling and decision making. With the trend towards increasing computational resources and larger datasets, machine learning has grown into an important skillset for the finance industry. This book is written for advanced graduate students and academics in financial econometrics, mathematical finance and applied statistics, in addition to quants and data scientists in the field of quantitative finance. Machine Learning in Finance: From Theory to Practice is divided into three parts, each part covering theory and applications. The first presents supervised learning for cross-sectional data from both a Bayesian and frequentist perspective. The more advanced material places a firm emphasis on neural networks, including deep learning, as well as Gaussian processes, with examples in investment management and derivative modeling. The second part presents supervised learning for time series data, arguably the most common data type used in finance with examples in trading, stochastic volatility and fixed income modeling. Finally, the third part presents reinforcement learning and its applications in trading, investment and wealth management. Python code examples are provided to support the readers' understanding of the methodologies and applications. The book also includes more than 80 mathematical and programming exercises, with worked solutions available to instructors. As a bridge to research in this emergent field, the final chapter presents the frontiers of machine learning in finance from a researcher's perspective, highlighting how many well-known concepts in statistical physics are likely to emerge as important methodologies for machine learning in finance.



Proceedings Of The 3rd Cognitive Mobility Conference


Proceedings Of The 3rd Cognitive Mobility Conference
DOWNLOAD
Author : Máté Zöldy
language : en
Publisher: Springer Nature
Release Date : 2025-02-24

Proceedings Of The 3rd Cognitive Mobility Conference written by Máté Zöldy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-24 with Computers categories.


This book introduces innovative methods and new insights, offering a comprehensive exploration of cognitive mobility's diverse dimensions. It discovers a pioneering perspective on cognitive mobility that redefines our understanding of this dynamic field. Integrating cutting-edge research and practical applications, it is an invaluable resource for academics and practitioners. Covering topics from theoretical foundations to real-world implementations, it provides a holistic understanding of cognitive mobility. Designed for researchers, educators, and practitioners, this book is an essential reference for deepening understanding and application of cognitive mobility concepts. Whether developing new technologies, educational programs, or conducting cognitive science research, this book offers the tools and insights needed to advance your work. Focusing on the latest developments and practical applications, it enriches understanding and empowers innovation in the field of cognitive mobility.



Machine Learning And Knowledge Discovery In Databases


Machine Learning And Knowledge Discovery In Databases
DOWNLOAD
Author : Massih-Reza Amini
language : en
Publisher: Springer Nature
Release Date : 2023-03-16

Machine Learning And Knowledge Discovery In Databases written by Massih-Reza Amini and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-16 with Computers categories.


The multi-volume set LNAI 13713 until 13718 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2022, which took place in Grenoble, France, in September 2022. The 236 full papers presented in these proceedings were carefully reviewed and selected from a total of 1060 submissions. In addition, the proceedings include 17 Demo Track contributions. The volumes are organized in topical sections as follows: Part I: Clustering and dimensionality reduction; anomaly detection; interpretability and explainability; ranking and recommender systems; transfer and multitask learning; Part II: Networks and graphs; knowledge graphs; social network analysis; graph neural networks; natural language processing and text mining; conversational systems; Part III: Deep learning; robust and adversarial machine learning; generative models; computer vision; meta-learning, neural architecture search; Part IV: Reinforcement learning; multi-agent reinforcement learning; bandits and online learning; active and semi-supervised learning; private and federated learning; Part V: Supervised learning; probabilistic inference; optimal transport; optimization; quantum, hardware; sustainability; Part VI: Time series; financial machine learning; applications; applications: transportation; demo track.



Advances In Manufacturing Technology Xxxiv


Advances In Manufacturing Technology Xxxiv
DOWNLOAD
Author : M. Shafik
language : en
Publisher: IOS Press
Release Date : 2021-09-23

Advances In Manufacturing Technology Xxxiv written by M. Shafik and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-23 with Technology & Engineering categories.


The development of technologies and management of operations is key to sustaining the success of manufacturing businesses, and since the late 1970s, the International Conference on Manufacturing Research (ICMR) has been a major annual event for academics and industrialists engaged in manufacturing research. The conference is renowned as a friendly and inclusive platform that brings together a broad community of researchers who share a common goal. This book presents the proceedings of ICMR2021, the 18th International Conference on Manufacturing Research, incorporating the 35th National Conference on Manufacturing Research, and held in Derby, UK, from 7 to 10 September 2021. The theme of the ICMR2021 conference is digital manufacturing. Within the context of Industrial 4.0, ICMR2021 provided a platform for researchers, academics and industrialists to share their vision, knowledge and experience, and to discuss emerging trends and new challenges in the field. The 60 papers included in the book are divided into 10 parts, each covering a different area of manufacturing research. These are: digital manufacturing, smart manufacturing; additive manufacturing; robotics and industrial automation; composite manufacturing; machining processes; product design and development; information and knowledge management; lean and quality management; and decision support and production optimization. The book will be of interest to all those involved in developing and managing new techniques in manufacturing industry.



Special Topics In Information Technology


Special Topics In Information Technology
DOWNLOAD
Author : Luigi Piroddi
language : en
Publisher: Springer Nature
Release Date : 2022-01-01

Special Topics In Information Technology written by Luigi Piroddi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-01 with Technology & Engineering categories.


This open access book presents thirteen outstanding doctoral dissertations in Information Technology from the Department of Electronics, Information and Bioengineering, Politecnico di Milano, Italy. Information Technology has always been highly interdisciplinary, as many aspects have to be considered in IT systems. The doctoral studies program in IT at Politecnico di Milano emphasizes this interdisciplinary nature, which is becoming more and more important in recent technological advances, in collaborative projects, and in the education of young researchers. Accordingly, the focus of advanced research is on pursuing a rigorous approach to specific research topics starting from a broad background in various areas of Information Technology, especially Computer Science and Engineering, Electronics, Systems and Control, and Telecommunications. Each year, more than 50 PhDs graduate from the program. This book gathers the outcomes of the thirteen best theses defended in 2020-21 and selected for the IT PhD Award. Each of the authors provides a chapter summarizing his/her findings, including an introduction, description of methods, main achievements and future work on the topic. Hence, the book provides a cutting-edge overview of the latest research trends in Information Technology at Politecnico di Milano, presented in an easy-to-read format that will also appeal to non-specialists.