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Opinion Mining and Sentiment Analysis
This survey covers techniques and approaches that promise to directly enable opinion-oriented information-seeking systems.
The Algorithmic Foundations of Differential Privacy
The problem of privacy-preserving data analysis has a long history spanning multiple disciplines. As electronic data about individuals becomes increasingly detailed, and as technology enables ever more powerful collection and curation of these data, the need increases for a robust, meaningful, and mathematically rigorous definition of privacy, together with a computationally rich class of algorithms that satisfy this definition. Differential Privacy is such a definition. The Algorithmic Foundations of Differential Privacy starts out by motivating and discussing the meaning of differential privacy, and proceeds to explore the fundamental techniques for achieving differential privacy, and the ...
Distributed Optimization and Statistical Learning Via the Alternating Direction Method of Multipliers
Surveys the theory and history of the alternating direction method of multipliers, and discusses its applications to a wide variety of statistical and machine learning problems of recent interest, including the lasso, sparse logistic regression, basis pursuit, covariance selection, support vector machines, and many others.
Information Systems Success Measurement
Information Systems Success Measurement presents a comprehensive review of the foundations, the trends, and the future challenges of IS success measurement in order to improve research and practice in terms of the measurement and evaluation of information systems. Information Systems Success Measurement explores the foundations and trends in the definition and measurement of information systems success. Starting with an introduction that examines how the concept of "effective" or "successful" information systems has progressed as information technology and its use has changed over the past 60 years. The authors introduce the DeLone and McLean Information Systems Success Model as an organizin...
Decision Forests
Presents a unified, efficient model of random decision forests which can be used in a number of applications such as scene recognition from photographs, object recognition in images, automatic diagnosis from radiological scans and document analysis.
Architecture of a Database System
Architecture of a Database System presents an architectural discussion of DBMS design principles, including process models, parallel architecture, storage system design, transaction system implementation, query processor and optimizer architectures, and typical shared components and utilities.
Computational Optimal Transport
The goal of Optimal Transport (OT) is to define geometric tools that are useful to compare probability distributions. Their use dates back to 1781. Recent years have witnessed a new revolution in the spread of OT, thanks to the emergence of approximate solvers that can scale to sizes and dimensions that are relevant to data sciences. Thanks to this newfound scalability, OT is being increasingly used to unlock various problems in imaging sciences (such as color or texture processing), computer vision and graphics (for shape manipulation) or machine learning (for regression, classification and density fitting). This monograph reviews OT with a bias toward numerical methods and their applicatio...
An Introduction to Variational Autoencoders
An Introduction to Variational Autoencoders provides a quick summary for the of a topic that has become an important tool in modern-day deep learning techniques.
Synopses for Massive Data
Describes basic principles and recent developments in approximate query processing. It focuses on four key synopses: random samples, histograms, wavelets, and sketches. It considers issues such as accuracy, space and time efficiency, optimality, practicality, range of applicability, error bounds on query answers, and incremental maintenance.
