Advanced Multimodal Compatibility Modeling And Recommendation
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Advanced Multimodal Compatibility Modeling And Recommendation
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Author : Weili Guan
language : en
Publisher: Springer Nature
Release Date : 2025-03-18
Advanced Multimodal Compatibility Modeling And Recommendation written by Weili Guan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-18 with Computers categories.
This Third Edition sheds light on state-of-the-art theories and practices in multimodal compatibility modeling and recommendation, offering comprehensive insights into this evolving field. This topic, and fashion compatibility modeling in particular, has garnered increasing research attention in recent years due to the significant economic impact of e-commerce. Building upon recent research and the prior edition, the authors present a series of graph-learning based multimodal compatibility modeling schemes, all of which have been proven to be effective over several public real-world datasets. This book introduces a number of advanced multimodal compatibility modeling and recommendation methods, including category-guided multimodal compatibility modeling and try-on-guided multimodal compatibility modeling. The authors also provide comprehensive solutions, including correlation-oriented graph learning, modality-oriented graph learning, unsupervised disentangled graph learning, partially supervised disentangled graph learning, and metapath-guided heterogeneous graph learning.
Graph Learning For Fashion Compatibility Modeling
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Author : Weili Guan
language : en
Publisher: Springer Nature
Release Date : 2022-11-02
Graph Learning For Fashion Compatibility Modeling written by Weili Guan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-02 with Computers categories.
This book sheds light on state-of-the-art theories for more challenging outfit compatibility modeling scenarios. In particular, this book presents several cutting-edge graph learning techniques that can be used for outfit compatibility modeling. Due to its remarkable economic value, fashion compatibility modeling has gained increasing research attention in recent years. Although great efforts have been dedicated to this research area, previous studies mainly focused on fashion compatibility modeling for outfits that only involved two items and overlooked the fact that each outfit may be composed of a variable number of items. This book develops a series of graph-learning based outfit compatibility modeling schemes, all of which have been proven to be effective over several public real-world datasets. This systematic approach benefits readers by introducing the techniques for compatibility modeling of outfits that involve a variable number of composing items. To deal with the challenging task of outfit compatibility modeling, this book provides comprehensive solutions, including correlation-oriented graph learning, modality-oriented graph learning, unsupervised disentangled graph learning, partially supervised disentangled graph learning, and metapath-guided heterogeneous graph learning. Moreover, this book sheds light on research frontiers that can inspire future research directions for scientists and researchers.
Catboost Algorithms And Applications
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Author : Richard Johnson
language : en
Publisher: HiTeX Press
Release Date : 2025-06-03
Catboost Algorithms And Applications written by Richard Johnson and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-03 with Computers categories.
"CatBoost Algorithms and Applications" "CatBoost Algorithms and Applications" offers a comprehensive and rigorous exploration of one of the most advanced gradient boosting frameworks in modern machine learning. The book begins with a deep dive into the mathematical foundations of CatBoost, dissecting key techniques such as ordered boosting, sophisticated handling of categorical variables, robust overfitting prevention, and the formal structure of symmetric trees. It unpacks CatBoost's internal mechanics, guiding the reader through the algorithm’s entire processing pipeline, memory and GPU optimizations, permutation policies, and extensibility for custom objectives — equipping practitioners with both theoretical mastery and practical insight. Building on these foundations, the book delves into advanced topics critical for real-world applications, including feature engineering, multimodal data integration, hyperparameter optimization, and automated machine learning workflows. Special emphasis is placed on model interpretability, fairness, and explainability, with dedicated chapters on SHAP values, bias assessment, model debugging, and governance—all vital for deploying responsible AI solutions. Readers will also learn to harness CatBoost at scale, with detailed architectures for distributed training, cloud deployment, resource management, and resilient production systems that support low-latency, high-throughput inference. Enriched with practical case studies, best practices, and guidance for emerging domains like time series forecasting and text data, "CatBoost Algorithms and Applications" culminates in an analysis of the latest research, current challenges, and the future trajectory of CatBoost in federated, privacy-preserving, and responsible machine learning. Designed for data scientists, engineers, and researchers, this book serves as both a definitive technical reference and a strategic resource for leveraging CatBoost to solve complex, enterprise-scale machine learning problems.
Recommender Systems Handbook
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Author : Francesco Ricci
language : en
Publisher: Springer Nature
Release Date : 2022-04-21
Recommender Systems Handbook written by Francesco Ricci and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-21 with Computers categories.
This third edition handbook describes in detail the classical methods as well as extensions and novel approaches that were more recently introduced within this field. It consists of five parts: general recommendation techniques, special recommendation techniques, value and impact of recommender systems, human computer interaction, and applications. The first part presents the most popular and fundamental techniques currently used for building recommender systems, such as collaborative filtering, semantic-based methods, recommender systems based on implicit feedback, neural networks and context-aware methods. The second part of this handbook introduces more advanced recommendation techniques, such as session-based recommender systems, adversarial machine learning for recommender systems, group recommendation techniques, reciprocal recommenders systems, natural language techniques for recommender systems and cross-domain approaches to recommender systems. The third part covers a wide perspective to the evaluation of recommender systems with papers on methods for evaluating recommender systems, their value and impact, the multi-stakeholder perspective of recommender systems, the analysis of the fairness, novelty and diversity in recommender systems. The fourth part contains a few chapters on the human computer dimension of recommender systems, with research on the role of explanation, the user personality and how to effectively support individual and group decision with recommender systems. The last part focusses on application in several important areas, such as, food, music, fashion and multimedia recommendation. This informative third edition handbook provides a comprehensive, yet concise and convenient reference source to recommender systems for researchers and advanced-level students focused on computer science and data science. Professionals working in data analytics that are using recommendation and personalization techniques will also find this handbook a useful tool.
Explainable Recommendation
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Author : Yongfeng Zhang
language : en
Publisher:
Release Date : 2020-03-10
Explainable Recommendation written by Yongfeng Zhang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-10 with Computers categories.
In recent years, a large number of explainable recommendation approaches have been proposed and applied in real-world systems. This survey provides a comprehensive review of the explainable recommendation research.
Openai Gpt For Python Developers
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Author : Aymen El Amri
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-05-21
Openai Gpt For Python Developers written by Aymen El Amri and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-21 with Technology & Engineering categories.
"OpenAI GPT for Python Developers" is your comprehensive guide to mastering the integration of OpenAI's GPT models into your Python projects, enhancing applications with various AI capabilities from chat completions to AI avatars. Key Features Strategies for optimizing and personalizing GPT models for specific applications. Insights into integrating additional OpenAI technologies like Whisper and Weaviate. Strong emphasis on responsible AI development and deployment. Book Description“OpenAI GPT for Python Developers” is meticulously crafted to provide Python developers with a deep dive into the mechanics and applications of GPT technology, beginning with a captivating narrative on the evolution of OpenAI and the fundamental workings of GPT models. As readers progress, they will be expertly guided through the essential steps of setting up a development environment tailored for AI innovations, coupled with insightful advice on selecting the most appropriate GPT model to suit specific project needs. The guide progresses into practical tutorials that cover the implementation of chat completions and the art of prompt engineering, providing a solid foundation in harnessing the capabilities of GPT for generating human-like text responses. Practical applications are further expanded with discussions on the creation of autonomous AI-to-AI dialogues, the development of AI avatars, and the strategic use of AI in interactive applications. In addition to technical skills, this book addresses the ethical implications and prospects of AI technologies, encouraging a holistic view of AI development. The guide is enriched with detailed examples, step-by-step tutorials, and comprehensive explanations that illuminate the theoretical aspects and emphasize practical implementation.What you will learn Set up the development environment for OpenAI GPT. Understand and choose the right GPT model for your needs. Implement advanced prompt engineering techniques. Explore embedding and advanced embedding examples. Utilize OpenAI's Whisper for speech recognition and translation. Integrate OpenAI TTS models for text-to-speech applications. Who this book is for This book is designed for readers at an intermediate to advanced level who have a basic understanding of machine learning concepts and are eager to expand their expertise in AI with a focus on OpenAI's technologies. Ideal for those involved in AI-driven projects, the book assumes familiarity with Python programming and a fundamental grasp of AI principles. It’s especially beneficial for developers aiming to integrate GPT models into applications, AI researchers, and technical professionals involved in AI product development.
Multimodal Fusion Technologies And Applications In The Context Of Neuroscience
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Author : Xiaomao Fan
language : en
Publisher: Frontiers Media SA
Release Date : 2023-06-08
Multimodal Fusion Technologies And Applications In The Context Of Neuroscience written by Xiaomao Fan and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-08 with Science categories.
Artificial Intelligence And Multimodal Signal Processing In Human Machine Interaction
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Author : Abdulhamit Subasi
language : en
Publisher: Elsevier
Release Date : 2024-09-18
Artificial Intelligence And Multimodal Signal Processing In Human Machine Interaction written by Abdulhamit Subasi and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-18 with Science categories.
Artificial Intelligence and Multimodal Signal Processing in Human-Machine Interaction presents an overview of an emerging field that is concerned with exploiting multiple modalities of communication in both Artificial Intelligence and Human-Machine Interaction. The book not only provides cross disciplinary research in the fields of multimodal signal acquisition and sensing, analysis, IoTs (Internet of Things), Artificial Intelligence, and system architectures, it also evaluates the role of Artificial Intelligence I in relation to the realization of contemporary Human Machine Interaction (HMI) systems.Readers are introduced to the multimodal signals and their role in the identification of the intended subjects, mental state and the realization of HMI systems are explored, and the applications of signal processing and machine/ensemble/deep learning for HMIs are assessed. A description of proposed methodologies is provided, and related works are also presented. This is a valuable resource for researchers, health professionals, postgraduate students, post doc researchers and faculty members in the fields of HMIs, Brain-Computer Interface (BCI), Prosthesis, Computer vision, and Mental state estimation, and all those who wish to broaden their knowledge in the allied field. - Covers advances in the multimodal signal processing and artificial intelligence assistive HMIs - Presents theories, algorithms, realizations, applications, approaches, and challenges that will have their impact and contribution in the design and development of modern and effective HMI (Human Machine Interaction) system - Presents different aspects of the multimodal signals, from the sensing to analysis using hardware/software, and making use of machine/ensemble/deep learning in the intended problem-solving
Artificial Intelligence And Inclusive Education
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Author : Jeremy Knox
language : en
Publisher: Springer
Release Date : 2019-06-13
Artificial Intelligence And Inclusive Education written by Jeremy Knox and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-13 with Education categories.
This book brings together the fields of artificial intelligence (often known as A.I.) and inclusive education in order to speculate on the future of teaching and learning in increasingly diverse social, cultural, emotional, and linguistic educational contexts. This book addresses a pressing need to understand how future educational practices can promote equity and equality, while at the same time adopting A.I. systems that are oriented towards automation, standardisation and efficiency. The contributions in this edited volume appeal to scholars and students with an interest in forming a critical understanding of the development of A.I. for education, as well as an interest in how the processes of inclusive education might be shaped by future technologies. Grounded in theoretical engagement, establishing key challenges for future practice, and outlining the latest research, this book offers a comprehensive overview of the complex issues arising from the convergence of A.I. technologiesand the necessity of developing inclusive teaching and learning. To date, there has been little in the way of direct association between research and practice in these domains: A.I. has been a predominantly technical field of research and development, and while intelligent computer systems and ‘smart’ software are being increasingly applied in many areas of industry, economics, social life, and education itself, a specific engagement with the agenda of inclusion appears lacking. Although such technology offers exciting possibilities for education, including software that is designed to ‘personalise’ learning or adapt to learner behaviours, these developments are accompanied by growing concerns about the in-built biases involved in machine learning techniques driven by ‘big data’.
Advanced Concepts For Intelligent Vision Systems
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Author : Sebastiano Battiato
language : en
Publisher: Springer
Release Date : 2015-10-07
Advanced Concepts For Intelligent Vision Systems written by Sebastiano Battiato and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-07 with Computers categories.
This book constitutes the thoroughly refereed proceedings of the 16th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2015, held Catania, Italy, in October 2015. The 76 revised full papers were carefully selected from 129 submissions. Acivs 2015 is a conference focusing on techniques for building adaptive, intelligent, safe and secure imaging systems. The focus of the conference is on following topic: low-level Image processing, video processing and camera networks, motion and tracking, security, forensics and biometrics, depth and 3D, image quality improvement and assessment, classification and recognition, multidimensional signal processing, multimedia compression, retrieval, and navigation.