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Author: Amos Fiat
Publisher:
ISBN: 9783662179291
Category :
Languages : en
Pages : 460
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Book Description
Author: Amos Fiat
Publisher:
ISBN: 9783662179291
Category :
Languages : en
Pages : 460
Get Book Here
Book Description
Author: Allan Borodin
Publisher: Cambridge University Press
ISBN: 9780521619462
Category : Computers
Languages : en
Pages : 440
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Book Description
Contains theoretical foundations, applications, and examples of competitive analysis for online algorithms.
Author: Rahul Vaze
Publisher: Cambridge University Press
ISBN: 1009358723
Category : Computers
Languages : en
Pages : 490
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Book Description
This textbook provides a rigorous introduction to online algorithms for graduate and senior undergraduate students. In-depth coverage of most of the important topics is presented with special emphasis on elegant analysis. A wide range of solved examples and practice exercises are included, allowing hands-on exposure to the basic concepts.
Author: Bin Li
Publisher: CRC Press
ISBN: 1482249642
Category : Business & Economics
Languages : en
Pages : 227
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Book Description
With the aim to sequentially determine optimal allocations across a set of assets, Online Portfolio Selection (OLPS) has significantly reshaped the financial investment landscape. Online Portfolio Selection: Principles and Algorithms supplies a comprehensive survey of existing OLPS principles and presents a collection of innovative strategies that leverage machine learning techniques for financial investment. The book presents four new algorithms based on machine learning techniques that were designed by the authors, as well as a new back-test system they developed for evaluating trading strategy effectiveness. The book uses simulations with real market data to illustrate the trading strategies in action and to provide readers with the confidence to deploy the strategies themselves. The book is presented in five sections that: Introduce OLPS and formulate OLPS as a sequential decision task Present key OLPS principles, including benchmarks, follow the winner, follow the loser, pattern matching, and meta-learning Detail four innovative OLPS algorithms based on cutting-edge machine learning techniques Provide a toolbox for evaluating the OLPS algorithms and present empirical studies comparing the proposed algorithms with the state of the art Investigate possible future directions Complete with a back-test system that uses historical data to evaluate the performance of trading strategies, as well as MATLAB® code for the back-test systems, this book is an ideal resource for graduate students in finance, computer science, and statistics. It is also suitable for researchers and engineers interested in computational investment. Readers are encouraged to visit the authors’ website for updates: http://olps.stevenhoi.org.
Author: Safiya Umoja Noble
Publisher: NYU Press
ISBN: 1479837245
Category : Computers
Languages : en
Pages : 245
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Book Description
Acknowledgments -- Introduction: the power of algorithms -- A society, searching -- Searching for Black girls -- Searching for people and communities -- Searching for protections from search engines -- The future of knowledge in the public -- The future of information culture -- Conclusion: algorithms of oppression -- Epilogue -- Notes -- Bibliography -- Index -- About the author
Author: Niv Buchbinder
Publisher: Now Publishers Inc
ISBN: 160198216X
Category : Computers
Languages : en
Pages : 190
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Book Description
Extends the primal-dual method to the setting of online algorithms, and shows its applicability to a wide variety of fundamental problems.
Author: Dennis Komm
Publisher: Springer
ISBN: 3319427490
Category : Computers
Languages : en
Pages : 360
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Book Description
This textbook explains online computation in different settings, with particular emphasis on randomization and advice complexity. These settings are analyzed for various online problems such as the paging problem, the k-server problem, job shop scheduling, the knapsack problem, the bit guessing problem, and problems on graphs. This book is appropriate for undergraduate and graduate students of computer science, assuming a basic knowledge in algorithmics and discrete mathematics. Also researchers will find this a valuable reference for the recent field of advice complexity.
Author: Mykel J. Kochenderfer
Publisher: MIT Press
ISBN: 0262047012
Category : Computers
Languages : en
Pages : 701
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Book Description
A broad introduction to algorithms for decision making under uncertainty, introducing the underlying mathematical problem formulations and the algorithms for solving them. Automated decision-making systems or decision-support systems—used in applications that range from aircraft collision avoidance to breast cancer screening—must be designed to account for various sources of uncertainty while carefully balancing multiple objectives. This textbook provides a broad introduction to algorithms for decision making under uncertainty, covering the underlying mathematical problem formulations and the algorithms for solving them. The book first addresses the problem of reasoning about uncertainty and objectives in simple decisions at a single point in time, and then turns to sequential decision problems in stochastic environments where the outcomes of our actions are uncertain. It goes on to address model uncertainty, when we do not start with a known model and must learn how to act through interaction with the environment; state uncertainty, in which we do not know the current state of the environment due to imperfect perceptual information; and decision contexts involving multiple agents. The book focuses primarily on planning and reinforcement learning, although some of the techniques presented draw on elements of supervised learning and optimization. Algorithms are implemented in the Julia programming language. Figures, examples, and exercises convey the intuition behind the various approaches presented.
Author: Evripidis Bampis
Publisher: Springer Science & Business Media
ISBN: 3540939792
Category : Computers
Languages : en
Pages : 302
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Book Description
The 6th Workshop on Approximation and Online Algorithms (WAOA 2008) focused on the design and analysis of algorithms for online and computati- ally hard problems. Both kinds of problems have a large number of appli- tions from a variety of ?elds. WAOA 2008 took place in Karlsruhe, Germany, during September 18–19, 2008. The workshop was part of the ALGO 2008 event that also hosted ESA 2008, WABI 2008, and ATMOS 2008. The pre- ous WAOA workshops were held in Budapest (2003), Rome (2004), Palma de Mallorca (2005), Zurich (2006), and Eilat (2007). The proceedings of these p- viousWAOA workshopsappearedasLNCS volumes2909,3351,3879,4368,and 4927, respectively. Topics of interest for WAOA 2008 were: algorithmic game theory, appro- mation classes, coloring and partitioning, competitive analysis, computational ?nance, cuts and connectivity, geometric problems, inapproximability results, mechanism design, network design, packing and covering, paradigms for design and analysis of approximationand online algorithms, randomizationtechniques, real-world applications, and scheduling problems. In response to the call for - pers,wereceived56submissions.Eachsubmissionwasreviewedbyatleastthree referees, and the vast majority by at least four referees. The submissions were mainly judged on originality, technical quality, and relevance to the topics of the conference. Based on the reviews, the Program Committee selected 22 papers. We are grateful to Andrei Voronkov for providing the EasyChair conference system,whichwasusedtomanagetheelectronicsubmissions,thereviewprocess, and the electronic PC meeting. It made our task much easier. We would also like to thank all the authors who submitted papers to WAOA 2008 as well as the local organizers of ALGO 2008.
Author: Phillip Compeau
Publisher:
ISBN: 9780990374633
Category :
Languages : en
Pages :
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Book Description
Bioinformatics Algorithms: an Active Learning Approach is one of the first textbooks to emerge from the recent Massive Online Open Course (MOOC) revolution. A light-hearted and analogy-filled companion to the authors' acclaimed online course (http://coursera.org/course/bioinformatics), this book presents students with a dynamic approach to learning bioinformatics. It strikes a unique balance between practical challenges in modern biology and fundamental algorithmic ideas, thus capturing the interest of students of biology and computer science students alike.Each chapter begins with a central biological question, such as "Are There Fragile Regions in the Human Genome?" or "Which DNA Patterns Play the Role of Molecular Clocks?" and then steadily develops the algorithmic sophistication required to answer this question. Hundreds of exercises are incorporated directly into the text as soon as they are needed; readers can test their knowledge through automated coding challenges on Rosalind (http://rosalind.info), an online platform for learning bioinformatics.The textbook website (http://bioinformaticsalgorithms.org) directs readers toward additional educational materials, including video lectures and PowerPoint slides.
