Search results for ""now publishers Inc""

Among the data structures commonly used in machine learning, graphs are arguably one of the most general. Graphs allow the modelling of complex objects, each of which can be annotated by metadata. Nonetheless, seemingly simple questions, such as determining whether two graphs are identical or whether one graph is contained in another graph, are remarkably hard to solve in practice. Machine learning methods operating on graphs must therefore grapple with the need to balance computational tractability with the ability to leverage as much of the information conveyed by each graph as possible. In the last 15 years, numerous graph kernels have been proposed to solve this problem, thereby making it possible to perform predictions in both classification and regression settings.This monograph provides a review of existing graph kernels, their applications, software plus data resources, and an empirical comparison of state-of-the-art graph kernels. It is divided into two parts: the first part focuses on the theoretical description of common graph kernels; the second part focuses on a large-scale empirical evaluation of graph kernels, as well as a description of desirable properties and requirements for benchmark data sets. Finally, the authors outline the future trends and open challenges for graph kernels. Written for every researcher, practitioner and student of machine learning, Graph Kernels provides a comprehensive and insightful survey of the various graph kernals available today. It gives the reader a detailed typology, and analysis of relevant graph kernels while exposing the relations between them and commenting on their applicability for specific data types. There is also a large-scale empirical evaluation of graph kernels.

Read more less

Financing Entrepreneurship and Innovation in China provides an overview of the current state-of-affairs in the financing of private innovations in China. While country-level innovation can take many forms, the focus is on the funding of business start-ups and entrepreneurial ventures. The monograph has four specific objectives: (1) to present an economic framework for evaluating the central challenges associated with the financing of entrepreneurial ventures in China, (2) to evaluate the relative size and importance of the channels through which private initiatives for innovation in China are currently being funded, (3) to survey the academic evidence on potential financing constraints currently facing private initiatives in innovation, and (4) to discuss public policy implications that may arise from these findings, as well as to outline the type of future research that may best inform Chinese policy makers. After the introduction, Section 2 begins with a review of the central economic themes in entrepreneurial finance. Section 3 reviews the channels through which external funding now reach entrepreneurs in China. Section 4 further explores the problems engendered by China's IPO regulations. Section 5 summarizes the findings, discusses policy implications, and explores potential venues for future research. The authors conclude that China's current IPO regulations represent a serious impediment to two important near-term goals espoused by the Chinese government – to bring more high-technology firms back to mainland stock markets, and to be included at a meaningful weight in international stock indices, particularly the MSCI Emerging Market Index.

Read more less

Equipping machines with comprehensive knowledge of the world’s entities and their relationships has been a longstanding goal of AI. Over the last decade, large-scale knowledge bases, also known as knowledge graphs, have been automatically constructed from web contents and text sources, and have become a key asset for search engines. This machine knowledge can be harnessed to semantically interpret textual phrases in news, social media and web tables, and contributes to question answering, natural language processing and data analytics. This monograph surveys fundamental concepts and practical methods for creating and curating large knowledge bases. It covers models and methods for discovering and curating large knowledge bases from online content, with emphasis on semi-structured web pages with lists, tables etc., and unstructured text sources. Case studies on academic projects and industrial knowledge graphs complement the survey of concepts and methods. The intended audience is students and researchers interested in a wide spectrum of topics: from machine knowledge and data quality to machine learning and data science as well as applications in web content mining and natural language understanding. It will also be of interest to industrial practitioners working on semantic technologies for web, social media, or enterprise content.

Read more less

Development of formal proofs of correctness of programs can increase actual and perceived reliability and facilitate better understanding of program specifications and their underlying assumptions. Tools supporting such development have been available for over 40 years but have only recently seen wide practical use. Projects based on construction of machine-checked formal proofs are now reaching an unprecedented scale, comparable to large software projects, which leads to new challenges in proof development and maintenance. Despite its increasing importance, the field of proof engineering is seldom considered in its own right; related theories, techniques, and tools span many fields and venues.QED at Large covers the timeline and research literature concerning proof development for program verification, including theories, languages, and tools. It emphasizes challenges and breakthroughs at each stage in history and highlights challenges that are currently present due to the increasing scale of proof developments.This monograph is intended for use by researchers and students who are new to the field. It provides the reader with an insightful overview of the work that has led to modern-day techniques for formally verifying software. In times of increasing automation, this underpins many software systems so future trends are also highlighted.

Read more less

The Economic Impacts of the Advanced Encryption Standard, 1996-2017 evaluates the net social benefits of advanced encryption standards (AES). This is one of many areas where the National Institute for Standards and Technology (NIST) has promoted innovation and industrial competitiveness to ensure that public and private computer systems can protect the confidentiality, availability, and integrity of digital information in the face of ever more powerful computers and developments in the field of cryptography.After an introductory chapter, Chapter 2 provides the ABCs of cryptography as it applies to the AES and an introduction to the computer networks that employ encryption systems. It further delves into the evolution of NIST's role as the Federal Government's authority on the computer security of civilian-focused agencies, the AES competition (1997-2000), and subsequent cryptographic validation programs including what these validation programs reveal about the composition of the encryption product market. Chapter 3 characterizes how the AES program and subsequent dependent industry standards have functioned as economic policy tools that reduced the economic barriers of the 1990s to the development, commercialization, and application of cryptographic technologies, as well as their continuing indirect role in supporting the quality of encryption systems, reducing encryption system risks, and facilitating the growth of related industries. This chapter also places the AES program in an industrial organizational context by describing the economic value chain of which the AES program is a part. Chapter 4 discusses the selection of pre-survey interviews with subject matter experts, the design of the survey instrument, and survey execution. Chapter 5 describes survey results, compares selected qualitative survey findings to pre-survey expectations, describes the three-tiered approach to estimating economic impact in context of actual survey results, and reports the costs of NIST's AES program for 1996-2017. Chapter 6 presents the results of the three-tiered approach to estimating the overall economic impacts of the AES program. Chapter 7 provides a summary and conclusion of the analysis.

Read more less