Download or read book Bandit Algorithms in Information Retrieval written by Dorota Głowacka and published by . This book was released on 2019 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph provides an overview of bandit algorithms inspired by various aspects of Information Retrieval. It is accessible to anyone who has completed introductory to intermediate level courses in machine learning and/or statistics.
Download or read book Bandit Algorithms in Information Retrieval written by Dorota Glowacka and published by Foundations and Trends(r) in I. This book was released on 2019-05-23 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph provides an overview of bandit algorithms inspired by various aspects of Information Retrieval. It is accessible to anyone who has completed introductory to intermediate level courses in machine learning and/or statistics.
Download or read book Bandit Algorithms written by Tor Lattimore and published by Cambridge University Press. This book was released on 2020-07-16 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: Decision-making in the face of uncertainty is a significant challenge in machine learning, and the multi-armed bandit model is a commonly used framework to address it. This comprehensive and rigorous introduction to the multi-armed bandit problem examines all the major settings, including stochastic, adversarial, and Bayesian frameworks. A focus on both mathematical intuition and carefully worked proofs makes this an excellent reference for established researchers and a helpful resource for graduate students in computer science, engineering, statistics, applied mathematics and economics. Linear bandits receive special attention as one of the most useful models in applications, while other chapters are dedicated to combinatorial bandits, ranking, non-stationary problems, Thompson sampling and pure exploration. The book ends with a peek into the world beyond bandits with an introduction to partial monitoring and learning in Markov decision processes.
Download or read book Introduction to Multi Armed Bandits written by Aleksandrs Slivkins and published by . This book was released on 2019-10-31 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multi-armed bandits is a rich, multi-disciplinary area that has been studied since 1933, with a surge of activity in the past 10-15 years. This is the first book to provide a textbook like treatment of the subject.
Download or read book Dynamic Information Retrieval Modeling written by Grace Hui Yang and published by Springer Nature. This book was released on 2022-05-31 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data and human-computer information retrieval (HCIR) are changing IR. They capture the dynamic changes in the data and dynamic interactions of users with IR systems. A dynamic system is one which changes or adapts over time or a sequence of events. Many modern IR systems and data exhibit these characteristics which are largely ignored by conventional techniques. What is missing is an ability for the model to change over time and be responsive to stimulus. Documents, relevance, users and tasks all exhibit dynamic behavior that is captured in data sets typically collected over long time spans and models need to respond to these changes. Additionally, the size of modern datasets enforces limits on the amount of learning a system can achieve. Further to this, advances in IR interface, personalization and ad display demand models that can react to users in real time and in an intelligent, contextual way. In this book we provide a comprehensive and up-to-date introduction to Dynamic Information Retrieval Modeling, the statistical modeling of IR systems that can adapt to change. We define dynamics, what it means within the context of IR and highlight examples of problems where dynamics play an important role. We cover techniques ranging from classic relevance feedback to the latest applications of partially observable Markov decision processes (POMDPs) and a handful of useful algorithms and tools for solving IR problems incorporating dynamics. The theoretical component is based around the Markov Decision Process (MDP), a mathematical framework taken from the field of Artificial Intelligence (AI) that enables us to construct models that change according to sequential inputs. We define the framework and the algorithms commonly used to optimize over it and generalize it to the case where the inputs aren't reliable. We explore the topic of reinforcement learning more broadly and introduce another tool known as a Multi-Armed Bandit which is useful for cases where exploring model parameters is beneficial. Following this we introduce theories and algorithms which can be used to incorporate dynamics into an IR model before presenting an array of state-of-the-art research that already does, such as in the areas of session search and online advertising. Change is at the heart of modern Information Retrieval systems and this book will help equip the reader with the tools and knowledge needed to understand Dynamic Information Retrieval Modeling.
Download or read book Information Retrieval written by Pavel Braslavski and published by Springer. This book was released on 2015-12-09 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed proceedings of the 8th Russian Summer School on Information Retrieval, RuSSIR 2014, held in Nizhniy Novgorod, Russia, in August 2014. The volume includes 6 tutorial papers, summarizing lectures given at the event, and 8 revised papers from the school participants.The papers focus on various aspects of information retrieval.
Download or read book Advances in Information Retrieval written by Jaap Kamps and published by Springer Nature. This book was released on 2023-03-16 with total page 735 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set LNCS 13980, 13981 and 13982 constitutes the refereed proceedings of the 45th European Conference on IR Research, ECIR 2023, held in Dublin, Ireland, during April 2-6, 2023. The 65 full papers, 41 short papers, 19 demonstration papers, 12 reproducibility papers consortium papers, 7 tutorial papers, and 10 doctorial consortium papers were carefully reviewed and selected from 489 submissions. The book also contains, 8 workshop summaries and 13 CLEF Lab descriptions. The accepted papers cover the state of the art in information retrieval focusing on user aspects, system and foundational aspects, machine learning, applications, evaluation, new social and technical challenges, and other topics of direct or indirect relevance to search.
Download or read book Information Retrieval written by David A. Grossman and published by Springer Science & Business Media. This book was released on 2012-11-12 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interested in how an efficient search engine works? Want to know what algorithms are used to rank resulting documents in response to user requests? The authors answer these and other key information retrieval design and implementation questions. This book is not yet another high level text. Instead, algorithms are thoroughly described, making this book ideally suited for both computer science students and practitioners who work on search-related applications. As stated in the foreword, this book provides a current, broad, and detailed overview of the field and is the only one that does so. Examples are used throughout to illustrate the algorithms. The authors explain how a query is ranked against a document collection using either a single or a combination of retrieval strategies, and how an assortment of utilities are integrated into the query processing scheme to improve these rankings. Methods for building and compressing text indexes, querying and retrieving documents in multiple languages, and using parallel or distributed processing to expedite the search are likewise described. This edition is a major expansion of the one published in 1998. Besides updating the entire book with current techniques, it includes new sections on language models, cross-language information retrieval, peer-to-peer processing, XML search, mediators, and duplicate document detection.
Download or read book Neural Information Processing written by Minho Lee and published by Springer. This book was released on 2013-10-29 with total page 794 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three volume set LNCS 8226, LNCS 8227 and LNCS 8228 constitutes the proceedings of the 20th International Conference on Neural Information Processing, ICONIP 2013, held in Daegu, Korea, in November 2013. The 180 full and 75 poster papers presented together with 4 extended abstracts were carefully reviewed and selected from numerous submissions. These papers cover all major topics of theoretical research, empirical study and applications of neural information processing research. The specific topics covered are as follows: cognitive science and artificial intelligence; learning theory, algorithms and architectures; computational neuroscience and brain imaging; vision, speech and signal processing; control, robotics and hardware technologies and novel approaches and applications.
Download or read book Online Evaluation for Information Retrieval written by Katja Hofmann and published by . This book was released on 2016-06-07 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides a comprehensive overview of the topic. It shows how online evaluation is used for controlled experiments, segmenting them into experiment designs that allow absolute or relative quality assessments. It also includes an extensive discussion of recent work on data re-use, and experiment estimation based on historical data.
Download or read book Advances in Information Retrieval written by Maarten de Rijke and published by Springer. This book was released on 2014-03-24 with total page 830 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 36th European Conference on IR Research, ECIR 2014, held in Amsterdam, The Netherlands, in April 2014. The 33 full papers, 50 poster papers and 15 demonstrations presented in this volume were carefully reviewed and selected from 288 submissions. The papers are organized in the following topical sections: evaluation, recommendation, optimization, semantics, aggregation, queries, mining social media, digital libraries, efficiency, and information retrieval theory. Also included are 3 tutorial and 4 workshop presentations.
Download or read book Neural Information Processing written by Chu Kiong Loo and published by Springer. This book was released on 2014-11-06 with total page 635 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three volume set LNCS 8834, LNCS 8835, and LNCS 8836 constitutes the proceedings of the 21st International Conference on Neural Information Processing, ICONIP 2014, held in Kuching, Malaysia, in November 2014. The 231 full papers presented were carefully reviewed and selected from 375 submissions. The selected papers cover major topics of theoretical research, empirical study, and applications of neural information processing research. The 3 volumes represent topical sections containing articles on cognitive science, neural networks and learning systems, theory and design, applications, kernel and statistical methods, evolutionary computation and hybrid intelligent systems, signal and image processing, and special sessions intelligent systems for supporting decision, making processes, theories and applications, cognitive robotics, and learning systems for social network and web mining.
Download or read book Advances in Information Retrieval written by Nazli Goharian and published by Springer Nature. This book was released on with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Advances in Bias and Fairness in Information Retrieval written by Ludovico Boratto and published by Springer Nature. This book was released on 2023-08-22 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 4th International Workshop on Algorithmic Bias in Search and Recommendation, BIAS 2023, held in Dublin, Ireland, in April 2023. The 10 full papers and 4 short papers included in this book were carefully reviewed and selected from 36 submissions. The present recent research in the following topics: biases exploration and assessment; mitigation strategies against biases; biases in newly emerging domains of application, including healthcare, Wikipedia, and news, novel perspectives; and conceptualizations of biases in the context of generative models and graph neural networks.
Download or read book Click Models for Web Search written by Aleksandr Chuklin and published by Springer Nature. This book was released on 2022-05-31 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the rapid growth of web search in recent years the problem of modeling its users has started to attract more and more attention of the information retrieval community. This has several motivations. By building a model of user behavior we are essentially developing a better understanding of a user, which ultimately helps us to deliver a better search experience. A model of user behavior can also be used as a predictive device for non-observed items such as document relevance, which makes it useful for improving search result ranking. Finally, in many situations experimenting with real users is just infeasible and hence user simulations based on accurate models play an essential role in understanding the implications of algorithmic changes to search engine results or presentation changes to the search engine result page. In this survey we summarize advances in modeling user click behavior on a web search engine result page. We present simple click models as well as more complex models aimed at capturing non-trivial user behavior patterns on modern search engine result pages. We discuss how these models compare to each other, what challenges they have, and what ways there are to address these challenges. We also study the problem of evaluating click models and discuss the main applications of click models.
Download or read book Algorithms for Data and Computation Privacy written by Alex X. Liu and published by Springer Nature. This book was released on 2020-11-28 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the state-of-the-art algorithms for data and computation privacy. It mainly focuses on searchable symmetric encryption algorithms and privacy preserving multi-party computation algorithms. This book also introduces algorithms for breaking privacy, and gives intuition on how to design algorithm to counter privacy attacks. Some well-designed differential privacy algorithms are also included in this book. Driven by lower cost, higher reliability, better performance, and faster deployment, data and computing services are increasingly outsourced to clouds. In this computing paradigm, one often has to store privacy sensitive data at parties, that cannot fully trust and perform privacy sensitive computation with parties that again cannot fully trust. For both scenarios, preserving data privacy and computation privacy is extremely important. After the Facebook–Cambridge Analytical data scandal and the implementation of the General Data Protection Regulation by European Union, users are becoming more privacy aware and more concerned with their privacy in this digital world. This book targets database engineers, cloud computing engineers and researchers working in this field. Advanced-level students studying computer science and electrical engineering will also find this book useful as a reference or secondary text.
Download or read book Multi armed Bandit Problem and Application written by Djallel Bouneffouf and published by Djallel Bouneffouf. This book was released on 2023-03-14 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, the multi-armed bandit (MAB) framework has attracted a lot of attention in various applications, from recommender systems and information retrieval to healthcare and finance. This success is due to its stellar performance combined with attractive properties, such as learning from less feedback. The multiarmed bandit field is currently experiencing a renaissance, as novel problem settings and algorithms motivated by various practical applications are being introduced, building on top of the classical bandit problem. This book aims to provide a comprehensive review of top recent developments in multiple real-life applications of the multi-armed bandit. Specifically, we introduce a taxonomy of common MAB-based applications and summarize the state-of-the-art for each of those domains. Furthermore, we identify important current trends and provide new perspectives pertaining to the future of this burgeoning field.
