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Optimization Under Uncertainty
Modern decision models increasingly involve parameters that are unknown or uncertain. Uncertainty is typically modeled by probability distribution over possible realizations of some random parameters. In presence of high dimensional multivariate random variables, estimating the joint probability distributions is difficult, and optimization models are often simplified by assuming that the random variables are independent. Although popular, the effect of this heuristic on the solution quality was little understood. This thesis centers around the following question: "How much can the expected cost increase if the random variables are arbitrarily correlated?" We introduce a new concept of Correl...
Stochastic Analysis, Filtering, and Stochastic Optimization
This volume is a collection of research works to honor the late Professor Mark H.A. Davis, whose pioneering work in the areas of Stochastic Processes, Filtering, and Stochastic Optimization spans more than five decades. Invited authors include his dissertation advisor, past collaborators, colleagues, mentees, and graduate students of Professor Davis, as well as scholars who have worked in the above areas. Their contributions may expand upon topics in piecewise deterministic processes, pathwise stochastic calculus, martingale methods in stochastic optimization, filtering, mean-field games, time-inconsistency, as well as impulse, singular, risk-sensitive and robust stochastic control.
The Elements of Joint Learning and Optimization in Operations Management
This book examines recent developments in Operations Management, and focuses on four major application areas: dynamic pricing, assortment optimization, supply chain and inventory management, and healthcare operations. Data-driven optimization in which real-time input of data is being used to simultaneously learn the (true) underlying model of a system and optimize its performance, is becoming increasingly important in the last few years, especially with the rise of Big Data.
Multi-armed Bandit Problem and Application
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.
Digital Privacy
During recent years, a continuously increasing amount of personal data has been made available through different websites around the world. Although the availability of personal information has created several advantages, it can be easily misused and may lead to violations of privacy. With growing interest in this area, Digital Privacy: Theory, Technologies, and Practices addresses this timely issue, providing information on state-of-the-art technologies, best practices, and research results, as well as legal, regulatory, and ethical issues. This book features contributions from experts in academia, industry, and government.
Internet and Network Economics
This volume contains the papers presented at the International Workshop on Internet and Network Economics held during December 17–20, 2008, in Sha- hai, China, for its fourth edition. WINE 2008 provided a forum for researchers from di?erent disciplines to communicate with each other and exchange their researching ?ndings in this emerging ?eld. WINE 2008hadteninvitedspeakers:FanChungGraham,MatthewJackson, Lawrence Lau, Tom Luo, Eric Maskin, Paul Milgrom, Christos Papadimitriou, Herbert Scarf, Hal Varian and Yinyu Ye. There were 126 submissions. Each submission was reviewed on average by 2. 5 Programme Committee members. The Committee decided to accept 68 papers. The programme also included ...
Database Systems for Advanced Applications
This book constitutes the refereed proceedings of the 9th International Conference on Database Systems for Advanced Applications, DASFAA 2004, held in Jeju Island, Korea in March 2004. The 60 revised full papers and 18 revised short papers presented together with 2 invited articles were carefully reviewed and seleted from 272 submissions. The papers are organized in topical sections on access methods, query processing in XML, security and integrity, query processing in temporal and spatial databases, semi-structured databases, knowledge discovery in temporal and spatial databases, XML and multimedia and knowledge discovery on the Web, query processing and optimization, classification and clustering, Web search, mobile databases, parallel and distributed databases, and multimedia databases.
Schistosomes and Schistosomiasis in South Asia
According to the author, the book addresses to all the scientists and not only to immunologists or biologists of European countries who are engaged in developing a vaccine, or a diagnostic kit or a new drug against the infection or on schistosome evolution. Even these scientists have to visit endemic countries for field trials or ask their counterparts to collect field data (which this book addresses ). Thus this book is not on molecular fundamentals but on the infection itself; how schistosome species are responding to the drug ; sensitivity and specificity of immunodiagnostic kits, antigen molecules; snail compatibility, production losses; schistosome evolution; schistosome outbreaks; complexities where more than two schistosome species are existing; problem of human schistosomiasis in South Asia etc In fact , all the topics of great interest to international scientists and scientists of endemic countries.
Event Mining
With a focus on computing system management, this book presents a variety of event mining approaches for improving the quality and efficiency of IT service and system management. It covers different components in the data-driven framework, from system monitoring and event generation to pattern discovery and summarization. The book explores recent developments in event mining, such as new clustering-based approaches, as well as various applications of event mining, including social media.
