Books published by now publishers Inc

Considers the cell-free network architecture that is designed to reach the goal of uniformly high data rates everywhere. The authors introduce the concept of a cell-free network before laying out the foundations of what is required to design and build such a network.

Tensor Regression is the first thorough overview of the fundamentals, motivations, popular algorithms, strategies for efficient implementation, related applications, available datasets, and software resources for tensor-based regression analysis.

Surveys fundamental concepts and practical methods for creating and curating large knowledge bases. The book covers models and methods for discovering and curating large knowledge bases from online content, with emphasis on semi-structured web pages and unstructured text sources.

Presents the body of econometric techniques that are customized to experimental applications. This monograph is aimed at two types of reader -- the experimental economist who is interested in expanding their skill set in econometric techniques and the econometrician interested in the econometric techniques currently being used by experimentalists.

Focuses on the CEO advice taking process and examines the case where advisers provide strategic advice to the top management of a firm. This review suggests that the process of business advice could be divided into attraction, engagement, exit and extension.

Being an inter-disciplinary subject, Signal Processing has application in almost all scientific fields. Applied Signal Processing links between the analogue and digital signal processing domains.

Reviews the existing literature on immigrant entrepreneurship by focusing on immigrant entrepreneurs' personal characteristics, their immigrant ethnic community networks, and the external ecosystem.

Failure to learn from past mistakes and successes has consistently been a major obstacle to improving IT project management. IT Project Management: Lessons Learned from Project Retrospectives 1999-2020 addresses this shortcoming by integrating, updating, and extending the research findings from four previous studies on IT project retrospectives.

Situates digital security within the broader landscape of social and political theories of security, and uses a critical security lens to encourage the reader to explore how digitally networked technologies are both included in and influenced by the co-creation of artefacts and practices in open environments.

Provides a review of existing graph kernels, their applications, software plus data resources, and an empirical comparison of state-of-the-art graph kernels. The book focuses on the theoretical description of common graph kernels, and on a large-scale empirical evaluation of graph kernels.

Presents a comprehensive statistical learning framework that uses Distributionally Robust Optimization (DRO) under the Wasserstein metric to ensure robustness to perturbationsin the data. The authors introduce the reader to the fundamental properties of the Wasserstein metric and the DRO formulation, before explaining the theory in detail.