Perturbations Optimization And Statistics
DOWNLOAD
Download Perturbations Optimization And Statistics PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Perturbations Optimization And Statistics book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Perturbations Optimization And Statistics
DOWNLOAD
Author : Tamir Hazan
language : en
Publisher: MIT Press
Release Date : 2023-12-05
Perturbations Optimization And Statistics written by Tamir Hazan and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-05 with Computers categories.
A description of perturbation-based methods developed in machine learning to augment novel optimization methods with strong statistical guarantees. In nearly all machine learning, decisions must be made given current knowledge. Surprisingly, making what is believed to be the best decision is not always the best strategy, even when learning in a supervised learning setting. An emerging body of work on learning under different rules applies perturbations to decision and learning procedures. These methods provide simple and highly efficient learning rules with improved theoretical guarantees. This book describes perturbation-based methods developed in machine learning to augment novel optimization methods with strong statistical guarantees, offering readers a state-of-the-art overview. Chapters address recent modeling ideas that have arisen within the perturbations framework, including Perturb & MAP, herding, and the use of neural networks to map generic noise to distribution over highly structured data. They describe new learning procedures for perturbation models, including an improved EM algorithm and a learning algorithm that aims to match moments of model samples to moments of data. They discuss understanding the relation of perturbation models to their traditional counterparts, with one chapter showing that the perturbations viewpoint can lead to new algorithms in the traditional setting. And they consider perturbation-based regularization in neural networks, offering a more complete understanding of dropout and studying perturbations in the context of deep neural networks.
Mathematical Programming With Data Perturbations
DOWNLOAD
Author : Anthony V. Fiacco
language : en
Publisher: CRC Press
Release Date : 2020-09-23
Mathematical Programming With Data Perturbations written by Anthony V. Fiacco and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-23 with Mathematics categories.
Presents research contributions and tutorial expositions on current methodologies for sensitivity, stability and approximation analyses of mathematical programming and related problem structures involving parameters. The text features up-to-date findings on important topics, covering such areas as the effect of perturbations on the performance of algorithms, approximation techniques for optimal control problems, and global error bounds for convex inequalities.
Statistics By Simulation
DOWNLOAD
Author : Carsten F. Dormann
language : en
Publisher: Princeton University Press
Release Date : 2025-06-03
Statistics By Simulation written by Carsten F. Dormann and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-03 with Computers categories.
An accessible guide to understanding statistics using simulations, with examples from a range of scientific disciplines Real-world challenges such as small sample sizes, skewed distributions of data, biased sampling designs, and more predictors than data points are pushing the limits of classical statistical analysis. This textbook provides a new tool for the statistical toolkit: data simulations. It shows that using simulation and data-generating models is an excellent way to validate statistical reasoning and to augment study design and statistical analysis with planning and visualization. Although data simulations are not new to professional statisticians, Statistics by Simulation makes the approach accessible to a broader audience, with examples from many fields. It introduces the reasoning behind data simulation and then shows how to apply it in planning experiments or observational studies, developing analytical workflows, deploying model diagnostics, and developing new indices and statistical methods. • Covers all steps of statistical practice, from planning projects to post-hoc analysis and model checking • Provides examples from disciplines including sociology, psychology, ecology, economics, physics, and medicine • Includes R code for all examples, with data and code freely available online • Offers bullet-point outlines and summaries of each chapter • Minimizes the use of jargon and requires only basic statistical background and skills
Beyond The Worst Case Analysis Of Algorithms
DOWNLOAD
Author : Tim Roughgarden
language : en
Publisher: Cambridge University Press
Release Date : 2021-01-14
Beyond The Worst Case Analysis Of Algorithms written by Tim Roughgarden and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-14 with Computers categories.
Introduces exciting new methods for assessing algorithms for problems ranging from clustering to linear programming to neural networks.
Green Energy Efficient And Sustainable Networks
DOWNLOAD
Author : Josip Lorincz
language : en
Publisher: MDPI
Release Date : 2020-01-21
Green Energy Efficient And Sustainable Networks written by Josip Lorincz and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-21 with Technology & Engineering categories.
The book Green, Energy-Efficient and Sustainable Networks provides insights and solutions for a range of problems in the field of obtaining greener, energy-efficient, and sustainable networks. The book contains the outcomes of the Special Issue on “Green, Energy-Efficient and Sustainable Networks” of the Sensors journal. Seventeen high-quality papers published in the Special Issue have been collected and reproduced in this book, demonstrating significant achievements in the field. Among the published papers, one paper is an editorial and one is a review, while the remaining 15 works are research articles. The published papers are self-contained peer-reviewed scientific works that are authored by more than 75 different contributors with both academic and industry backgrounds. The editorial paper gives an introduction to the problem of information and communication technology (ICT) energy consumption and greenhouse gas emissions, presenting the state of the art and future trends in terms of improving the energy-efficiency of wireless networks and data centers, as the major energy consumers in the ICT sector. In addition, the published articles aim to improve energy efficiency in the fields of software-defined networking, Internet of things, machine learning, authentication, energy harvesting, wireless relay systems, routing metrics, wireless sensor networks, device-to-device communications, heterogeneous wireless networks, and image sensing. The last paper is a review that gives a detailed overview of energy-efficiency improvements and methods for the implementation of fifth-generation networks and beyond. This book can serve as a source of information in industrial, teaching, and/or research and development activities. The book is a valuable source of information, since it presents recent advances in different fields related to greening and improving the energy-efficiency and sustainability of those ICTs particularly addressed in this book
Computer Vision Eccv 2022
DOWNLOAD
Author : Shai Avidan
language : en
Publisher: Springer Nature
Release Date : 2022-11-10
Computer Vision Eccv 2022 written by Shai Avidan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-10 with Computers categories.
The 39-volume set, comprising the LNCS books 13661 until 13699, constitutes the refereed proceedings of the 17th European Conference on Computer Vision, ECCV 2022, held in Tel Aviv, Israel, during October 23–27, 2022. The 1645 papers presented in these proceedings were carefully reviewed and selected from a total of 5804 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.
Handbook Of Intelligent Automation Systems Using Computer Vision And Artificial Intelligence
DOWNLOAD
Author : Rupali Gill
language : en
Publisher: John Wiley & Sons
Release Date : 2025-09-03
Handbook Of Intelligent Automation Systems Using Computer Vision And Artificial Intelligence written by Rupali Gill and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-03 with Computers categories.
The book is essential for anyone seeking to understand and leverage the transformative power of intelligent automation technologies, providing crucial insights into current trends, challenges, and effective solutions that can significantly enhance operational efficiency and decision-making within organizations. Intelligent automation systems, also called cognitive automation, use automation technologies such as artificial intelligence, business process management, and robotic process automation, to streamline and scale decision-making across organizations. Intelligent automation simplifies processes, frees up resources, improves operational efficiencies, and has a variety of applications. Intelligent automation systems aim to reduce costs by augmenting the workforce and improving productivity and accuracy through consistent processes and approaches, which enhance quality, improve customer experience, and address compliance and regulations with confidence. Handbook of Intelligent Automation Systems Using Computer Vision and Artificial Intelligence explores the significant role, current trends, challenges, and potential solutions to existing challenges in the field of intelligent automation systems, making it an invaluable guide for researchers, industry professionals, and students looking to apply these innovative technologies. Readers will find the volume: Offers comprehensive coverage on intelligent automation systems using computer vision and AI, covering everything from foundational concepts to real-world applications and ethical considerations; Provides actionable knowledge with case studies and best practices for intelligent automation systems, computer vision, and AI; Explores the integration of various techniques, including facial recognition, natural language processing, neuroscience and neuromarketing. Audience The book is designed for AI and data scientists, software developers and engineers in industry and academia, as well as business leaders and entrepreneurs who are interested in the applications of intelligent automation systems.
Security And Privacy In Communication Networks
DOWNLOAD
Author : Songqing Chen
language : en
Publisher: Springer Nature
Release Date : 2019-12-10
Security And Privacy In Communication Networks written by Songqing Chen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-10 with Computers categories.
This two-volume set LNICST 304-305 constitutes the post-conference proceedings of the 15thInternational Conference on Security and Privacy in Communication Networks, SecureComm 2019, held in Orlando, FL, USA, in October 2019. The 38 full and 18 short papers were carefully reviewed and selected from 149 submissions. The papers are organized in topical sections on blockchains, internet of things, machine learning, everything traffic security communicating covertly, let’s talk privacy, deep analysis, systematic theory, bulletproof defenses, blockchains and IoT, security and analytics, machine learning, private, better clouds, ATCS workshop.
Adversary Aware Learning Techniques And Trends In Cybersecurity
DOWNLOAD
Author : Prithviraj Dasgupta
language : en
Publisher: Springer Nature
Release Date : 2021-01-22
Adversary Aware Learning Techniques And Trends In Cybersecurity written by Prithviraj Dasgupta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-22 with Computers categories.
This book is intended to give researchers and practitioners in the cross-cutting fields of artificial intelligence, machine learning (AI/ML) and cyber security up-to-date and in-depth knowledge of recent techniques for improving the vulnerabilities of AI/ML systems against attacks from malicious adversaries. The ten chapters in this book, written by eminent researchers in AI/ML and cyber-security, span diverse, yet inter-related topics including game playing AI and game theory as defenses against attacks on AI/ML systems, methods for effectively addressing vulnerabilities of AI/ML operating in large, distributed environments like Internet of Things (IoT) with diverse data modalities, and, techniques to enable AI/ML systems to intelligently interact with humans that could be malicious adversaries and/or benign teammates. Readers of this book will be equipped with definitive information on recent developments suitable for countering adversarial threats in AI/ML systems towards making them operate in a safe, reliable and seamless manner.
Backdoor Attacks Against Learning Based Algorithms
DOWNLOAD
Author : Shaofeng Li
language : en
Publisher: Springer Nature
Release Date : 2024-05-29
Backdoor Attacks Against Learning Based Algorithms written by Shaofeng Li and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-29 with Computers categories.
This book introduces a new type of data poisoning attack, dubbed, backdoor attack. In backdoor attacks, an attacker can train the model with poisoned data to obtain a model that performs well on a normal input but behaves wrongly with crafted triggers. Backdoor attacks can occur in many scenarios where the training process is not entirely controlled, such as using third-party datasets, third-party platforms for training, or directly calling models provided by third parties. Due to the enormous threat that backdoor attacks pose to model supply chain security, they have received widespread attention from academia and industry. This book focuses on exploiting backdoor attacks in the three types of DNN applications, which are image classification, natural language processing, and federated learning. Based on the observation that DNN models are vulnerable to small perturbations, this book demonstrates that steganography and regularization can be adopted to enhance the invisibility of backdoor triggers. Based on image similarity measurement, this book presents two metrics to quantitatively measure the invisibility of backdoor triggers. The invisible trigger design scheme introduced in this book achieves a balance between the invisibility and the effectiveness of backdoor attacks. In the natural language processing domain, it is difficult to design and insert a general backdoor in a manner imperceptible to humans. Any corruption to the textual data (e.g., misspelled words or randomly inserted trigger words/sentences) must retain context-awareness and readability to human inspectors. This book introduces two novel hidden backdoor attacks, targeting three major natural language processing tasks, including toxic comment detection, neural machine translation, and question answering, depending on whether the targeted NLP platform accepts raw Unicode characters. The emerged distributed training framework, i.e., federated learning, has advantages in preserving users' privacy. It has been widely used in electronic medical applications, however, it also faced threats derived from backdoor attacks. This book presents a novel backdoor detection framework in FL-based e-Health systems. We hope this book can provide insightful lights on understanding the backdoor attacks in different types of learning-based algorithms, including computer vision, natural language processing, and federated learning. The systematic principle in this book also offers valuable guidance on the defense of backdoor attacks against future learning-based algorithms.