Welcome to our book review site go-pdf.online!
You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
Program Synthesis
Program synthesis is the task of automatically finding a program in the underlying programming language that satisfies the user intent expressed in the form of some specification. Since the inception of artificial intelligence in the 1950s, this problem has been considered the holy grail of Computer Science. Despite inherent challenges in the problem such as ambiguity of user intent and a typically enormous search space of programs, the field of program synthesis has developed many different techniques that enable program synthesis in different real-life application domains. It is now used successfully in software engineering, biological discovery, compute-raided education, end-user programm...
Neurosymbolic Programming
Neurosymbolic programming is an emerging area that bridges the areas of deep learning and program synthesis. As in classical machine learning, the goal is to learn functions from data. However, these functions are represented as programs that can use neural modules in addition to symbolic primitives and are induced using a combination of symbolic search and gradient-based optimization.Neurosymbolic programming can offer multiple advantages over end-to-end deep learning. Programs can sometimes naturally represent long-horizon, procedural tasks that are difficult to perform using deep networks. Neurosymbolic representations are also, commonly, easier to interpret and formally verify than neura...
A Framework for Mass-market Inductive Program Synthesis
Programming by examples (PBE), or inductive program synthesis, is a problem of finding a program in the underlying domain-specific language (DSL) that is consistent with the given input-output examples or constraints. In the last decade, it has gained a lot of prominence thanks to the mass-market deployments of several PBE-based technologies for data wrangling - the widespread problem of transforming raw datasets into a structured form, more amenable to analysis. However, deployment of a mass-market application of program synthesis is challenging. First, an efficient implementation requires non-trivial engineering insight, often overlooked in a research prototype. This insight takes the form...
NEUROSYMBOLIC PROGRAMMING
Neurosymbolic programming is an emerging area that bridges the areas of deep learning and program synthesis. As in classical machine learning, the goal is to learn functions from data. However, these functions are represented as programs that can use neural modules in addition to symbolic primitives and are induced using a combination of symbolic search and gradient-based optimization. Neurosymbolic programming can offer multiple advantages over end-to-end deep learning. Programs can sometimes naturally represent long-horizon, procedural tasks that are difficult to perform using deep networks. Neurosymbolic representations are also, commonly, easier to interpret and formally verify than neur...
Natural Language Data Management and Interfaces
The volume of natural language text data has been rapidly increasing over the past two decades, due to factors such as the growth of the Web, the low cost associated with publishing, and the progress on the digitization of printed texts. This growth combined with the proliferation of natural language systems for search and retrieving information provides tremendous opportunities for studying some of the areas where database systems and natural language processing systems overlap. This book explores two interrelated and important areas of overlap: (1) managing natural language data and (2) developing natural language interfaces to databases. It presents relevant concepts and research question...
Algebraic Structures in Natural Language
Algebraic Structures in Natural Language addresses a central problem in cognitive science concerning the learning procedures through which humans acquire and represent natural language. Until recently algebraic systems have dominated the study of natural language in formal and computational linguistics, AI, and the psychology of language, with linguistic knowledge seen as encoded in formal grammars, model theories, proof theories and other rule-driven devices. Recent work on deep learning has produced an increasingly powerful set of general learning mechanisms which do not apply rule-based algebraic models of representation. The success of deep learning in NLP has led some researchers to que...
PROCEEDINGS OF THE 22ND CONFERENCE ON FORMAL METHODS IN COMPUTER-AIDED DESIGN – FMCAD 2022
The Conference on Formal Methods in Computer-Aided Design (FMCAD) is an annual conference on the theory and applications of formal methods in hardware and system in academia and industry for presenting and discussing groundbreaking methods, technologies, theoretical results, and tools for reasoning formally about computing systems. FMCAD covers formal aspects of computer-aided system testing.
Volcanism and Global Environmental Change
A multidisciplinary volume describing the effects of volcanism on the environment, past and present, for researchers and advanced students.
Handbook of Ratings
This handbook presents a systematic overview of approaches to, diversity, and problems involved in interdisciplinary rating methodologies. Historically, the purpose of ratings is to achieve information transparency regarding a given body’s activities, whether in the field of finance, banking, or sports for example. This book focuses on commonly used rating methods in three important fields: finance, sports, and the social sector. In the world of finance, investment decisions are largely shaped by how positively or negatively economies or financial instruments are rated. Ratings have thus become a basis of trust for investors. Similarly, sports evaluation and funding are largely based on co...
HHAI 2023: Augmenting Human Intellect
Artificial intelligence (AI) has been much in the news recently, with some commentators expressing concern that AI might eventually replace humans. But many developments in AI are designed to enhance and supplement the performance of humans rather than replace them, and a novel field of study, with new approaches and solutions to the development of AI, has arisen to focus on this aspect of the technology. This book presents the proceedings of HHAI2023, the 2nd International Conference on Hybrid Human-Artificial Intelligence, held from 26-30 June 2023, in Munich, Germany. The HHAI international conference series is focused on the study of artificially intelligent systems that cooperate synerg...
