Author: Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
"Secure and Trustworthy Machine Learning (SaTML), IEEE Conference On".
Author: 2023 IEEE Conference on Secure and Trustworthy Machine Learning
Author: 2024 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML)
Author: IEEE StaffPublisher:
ISBN:
Category : Technology & Engineering
Languages : en
Pages : 0
Book Description
This conference will expand on the theoretical and practical understandings of vulnerabilities inherent to ML systems, explore the robustness of ML algorithms and systems, and aid in developing a unified, coherent scientific community which aims to build trustworthy ML systems
Introduction to Generative AI
Author: Numa DhamaniPublisher: Simon and Schuster
ISBN: 1633437191
Category : Computers
Languages : en
Pages : 334
Book Description
Generative AI tools like ChatGPT are amazing—but how will their use impact our society? This book introduces the world-transforming technology and the strategies you need to use generative AI safely and effectively. Introduction to Generative AI gives you the hows-and-whys of generative AI in accessible language. In this easy-to-read introduction, you’ll learn: How large language models (LLMs) work How to integrate generative AI into your personal and professional workflows Balancing innovation and responsibility The social, legal, and policy landscape around generative AI Societal impacts of generative AI Where AI is going Anyone who uses ChatGPT for even a few minutes can tell that it’s truly different from other chatbots or question-and-answer tools. Introduction to Generative AI guides you from that first eye-opening interaction to how these powerful tools can transform your personal and professional life. In it, you’ll get no-nonsense guidance on generative AI fundamentals to help you understand what these models are (and aren’t) capable of, and how you can use them to your greatest advantage. Foreword by Sahar Massachi. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Generative AI tools like ChatGPT, Bing, and Bard have permanently transformed the way we work, learn, and communicate. This delightful book shows you exactly how Generative AI works in plain, jargon-free English, along with the insights you’ll need to use it safely and effectively. About the book Introduction to Generative AI guides you through benefits, risks, and limitations of Generative AI technology. You’ll discover how AI models learn and think, explore best practices for creating text and graphics, and consider the impact of AI on society, the economy, and the law. Along the way, you’ll practice strategies for getting accurate responses and even understand how to handle misuse and security threats. What's inside How large language models work Integrate Generative AI into your daily work Balance innovation and responsibility About the reader For anyone interested in Generative AI. No technical experience required. About the author Numa Dhamani is a natural language processing expert working at the intersection of technology and society. Maggie Engler is an engineer and researcher currently working on safety for large language models. The technical editor on this book was Maris Sekar. Table of Contents 1 Large language models: The power of AI Evolution of natural language processing 2 Training large language models 3 Data privacy and safety with LLMs 4 The evolution of created content 5 Misuse and adversarial attacks 6 Accelerating productivity: Machine-augmented work 7 Making social connections with chatbots 8 What’s next for AI and LLMs 9 Broadening the horizon: Exploratory topics in AI
Verification, Model Checking, and Abstract Interpretation
Author: Rayna DimitrovaPublisher: Springer Nature
ISBN: 3031505212
Category : Computers
Languages : en
Pages : 349
Book Description
The two-volume set LNCS 14499 and 14500 constitutes the proceedings of the 25th International Conference on Verification, Model Checking, and Abstract Interpretation, VMCAI 2024, which took place in London, Ontario, Canada, in January 2024. The 30 full papers presented in the proceedings were carefully reviewed and selected from 74 submissions. They were organized in topical sections as follows:Part I: Abstract interpretation; infinite-state systems; model checking and synthesis; SAT, SMT, and automated reasoning; Part II: Concurrency; neural networks; probabilistic and quantum programs; program and system verification; runtime verification; security and privacy;
Ethical Design of Artificial Intelligence-based Systems for Decision Making
Author: Valentina FranzoniPublisher: Frontiers Media SA
ISBN: 2832517145
Category : Science
Languages : en
Pages : 102
Book Description
Artificial Intelligence (AI), including Machine Learning with Deep Neural Networks, is making and supporting decisions in ways that increasingly affect humans in many aspects of their lives. Both autonomous and decision-support systems applying AI algorithms and data-driven models are used for decisions about justice, education, physical and psychological health, and to provide or deny access to credit, healthcare, and other essential resources, in all aspects of daily life, in increasingly ubiquitous and sometimes ambiguous ways. Too often these systems are built without considering the human factors associated with their use and the need for clarity about the correct way to use them, and possible biases. Models and systems provide results that are difficult to interpret and are accused of being good or bad, whereas good or bad is only the design of such tools, and the necessary training for them to be properly integrated into human values.
Explainable Artificial Intelligence
Author: Luca LongoPublisher: Springer Nature
ISBN: 303163800X
Category :
Languages : en
Pages : 471
Book Description
Machine Learning and Knowledge Discovery in Databases: Research Track
Author: Danai KoutraPublisher: Springer Nature
ISBN: 3031434188
Category : Computers
Languages : en
Pages : 754
Book Description
The multi-volume set LNAI 14169 until 14175 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2023, which took place in Turin, Italy, in September 2023. The 196 papers were selected from the 829 submissions for the Research Track, and 58 papers were selected from the 239 submissions for the Applied Data Science Track. The volumes are organized in topical sections as follows: Part I: Active Learning; Adversarial Machine Learning; Anomaly Detection; Applications; Bayesian Methods; Causality; Clustering. Part II: Computer Vision; Deep Learning; Fairness; Federated Learning; Few-shot learning; Generative Models; Graph Contrastive Learning. Part III: Graph Neural Networks; Graphs; Interpretability; Knowledge Graphs; Large-scale Learning. Part IV: Natural Language Processing; Neuro/Symbolic Learning; Optimization; Recommender Systems; Reinforcement Learning; Representation Learning. Part V: Robustness; Time Series; Transfer and Multitask Learning. Part VI: Applied Machine Learning; Computational Social Sciences; Finance; Hardware and Systems; Healthcare & Bioinformatics; Human-Computer Interaction; Recommendation and Information Retrieval. Part VII: Sustainability, Climate, and Environment.- Transportation & Urban Planning.- Demo.
Safe and Trustworthy Machine Learning
Author: Bhavya KailkhuraPublisher: Frontiers Media SA
ISBN: 2889714144
Category : Science
Languages : en
Pages : 101
Book Description
Machine Learning and Knowledge Discovery in Databases. Research Track
Author: Albert BifetPublisher: Springer Nature
ISBN: 3031703448
Category :
Languages : en
Pages : 513
Book Description