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Log-Linear Models, Extensions, and Applications
Advances in training models with log-linear structures, with topics including variable selection, the geometry of neural nets, and applications. Log-linear models play a key role in modern big data and machine learning applications. From simple binary classification models through partition functions, conditional random fields, and neural nets, log-linear structure is closely related to performance in certain applications and influences fitting techniques used to train models. This volume covers recent advances in training models with log-linear structures, covering the underlying geometry, optimization techniques, and multiple applications. The first chapter shows readers the inner workings...
Vectorization
Enables readers to develop foundational and advanced vectorization skills for scalable data science and machine learning and address real-world problems Offering insights across various domains such as computer vision and natural language processing, Vectorization covers the fundamental topics of vectorization including array and tensor operations, data wrangling, and batch processing. This book illustrates how the principles discussed lead to successful outcomes in machine learning projects, serving as concrete examples for the theories explained, with each chapter including practical case studies and code implementations using NumPy, TensorFlow, and PyTorch. Each chapter has one or two typ...
Text, Speech and Dialogue
Here are the refereed proceedings of the 9th International Conference on Text, Speech and Dialogue, TSD 2006. The book presents 87 revised full papers together with 2 invited papers reviewing state-of-the-art research in the field of natural language processing. Coverage ranges from theoretical and methodological issues to applications with special focus on corpora, texts and transcription, speech analysis, recognition and synthesis, as well as their intertwining within NL dialogue systems.
Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning
Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning Authoritative reference on the state of the art in the field with additional coverage of important foundational concepts Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning presents cutting-edge research advances in the rapidly growing areas in optical and RF electromagnetic device modeling, simulation, and inverse-design. The text provides a comprehensive treatment of the field on subjects ranging from fundamental theoretical principles and new technological developments to state-of-the-art device design, as well as examples encompassing a wide range of related sub-areas. The ...
A short guide to post-editing
Artificial intelligence is changing and will continue to change the world we live in. These changes are also influencing the translation market. Machine translation (MT) systems automatically transfer one language to another within seconds. However, MT systems are very often still not capable of producing perfect translations. To achieve high quality translations, the MT output first has to be corrected by a professional translator. This procedure is called post-editing (PE). PE has become an established task on the professional translation market. The aim of this text book is to provide basic knowledge about the most relevant topics in professional PE. The text book comprises ten chapters on both theoretical and practical aspects including topics like MT approaches and development, guidelines, integration into CAT tools, risks in PE, data security, practical decisions in the PE process, competences for PE, and new job profiles.
Machine Learning on Commodity Tiny Devices
This book aims at the tiny machine learning (TinyML) software and hardware synergy for edge intelligence applications. This book presents on-device learning techniques covering model-level neural network design, algorithm-level training optimization and hardware-level instruction acceleration. Analyzing the limitations of conventional in-cloud computing would reveal that on-device learning is a promising research direction to meet the requirements of edge intelligence applications. As to the cutting-edge research of TinyML, implementing a high-efficiency learning framework and enabling system-level acceleration is one of the most fundamental issues. This book presents a comprehensive discuss...
Guide to OCR for Arabic Scripts
This Guide to OCR for Arabic Scripts is the first book of its kind, specifically devoted to this emerging field. Topics and features: contains contributions from the leading researchers in the field; with a Foreword by Professor Bente Maegaard of the University of Copenhagen; presents a detailed overview of Arabic character recognition technology, covering a range of different aspects of pre-processing and feature extraction; reviews a broad selection of varying approaches, including HMM-based methods and a recognition system based on multidimensional recurrent neural networks; examines the evaluation of Arabic script recognition systems, discussing data collection and annotation, benchmarking strategies, and handwriting recognition competitions; describes numerous applications of Arabic script recognition technology, from historical Arabic manuscripts to online Arabic recognition.
8th URV Doctoral Workshop in Computer Science and Mathematics
This book contains the proceedings of the 8th Doctoral Workshop in Computer Science and Mathematics - DCSM 2023. It was celebrated in Universitat Rovira i Virgili (URV), Campus Sescelades, Tarragona, on May 3, 2023. The aim of this workshop is to promote the dissemination of ideas, methods, and results developed by the students of the PhD program in Computer Science and Mathematics from URV.
Issues in the Multilingual Information Processing of Spoken Political and Journalistic Texts
From television screens to mobile phones, spoken political and journalistic texts in the media are accessible to recipients of almost any kind, including the international public. These texts constitute a remarkable source of empirical data for human behaviour and for linguistic phenomena, but pose significant challenges in terms of their evaluation, processing and translation due to a set of distinctive characteristics. This volume presents and describes a number of features of spoken political and journalistic texts, and proposes strategies for their correct and efficient analysis and processing both by human evaluators and by Natural Language Processing applications. The book also discusses the accessibility of “complex” information content and transfer for an international audience, as well as the visibility of the speaker’s attitude and intentions.
