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Fairness Preserving Empirical Risk Minimization
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Book Synopsis Fairness-Preserving Empirical Risk Minimization by : Guanqun Yang
Download or read book Fairness-Preserving Empirical Risk Minimization written by Guanqun Yang and published by . This book was released on 2019 with total page 49 pages. Available in PDF, EPUB and Kindle. Book excerpt: The concerns regarding ramifications of societal bias targeted at a particular identity group (for example, gender or race) residing in algorithmic decision-making systems have been ever-growing in the past decade. It is a common practice of machine learning models' participation in these systems through empirical risk minimization (ERM) principle, which is often the cause of unfairness by trading off underrepresented groups for overall performance. Despite the importance of preserving fairness in such systems, there is hardly consensus in defining unified fairness metrics, designing widely-applicable bias-mitigation algorithms, and delivering interpretable models abiding by the ERM principle. The situation is made even more grievous when non-structural data, including text, image, and audio, is involved in these systems due to the unavailability of the well-defined identity attribute. Current approaches attempt to tackle algorithmic bias in non-structural settings from data itself and intermediate representation together with the inference component within models. In this thesis, we propose to unify all three bias-mitigation operations into one streamlined machine learning pipeline. At the same time, to provide interpretable results, the explorations will be made while carrying out debiasing procedures, and theoretical justifications will be provided accordingly. By ameliorating different bias-mitigation strategies through synergistic effects and addressing model transparency issues by investigating internal representations, we show that the proposed pipeline could provide interpretable machine learning models that embody fairness across different identity groups in numerous non-structural data settings.
Book Synopsis Advances in Computational Intelligence by : Ignacio Rojas
Download or read book Advances in Computational Intelligence written by Ignacio Rojas and published by Springer Nature. This book was released on 2023-11-03 with total page 723 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set LNCS 14134 and LNCS 14135 constitutes the refereed proceedings of the 17th International Work-Conference on Artificial Neural Networks, IWANN 2023, held in Ponta Delgada, Portugal, during June 19–21, 2023. The 108 full papers presented in this two-volume set were carefully reviewed and selected from 149 submissions. The papers in Part I are organized in topical sections on advanced topics in computational intelligence; advances in artificial neural networks; ANN HW-accelerators; applications of machine learning in biomedicine and healthcare; and applications of machine learning in time series analysis. The papers in Part II are organized in topical sections on deep learning and applications; deep learning applied to computer vision and robotics; general applications of artificial intelligence; interaction with neural systems in both health and disease; machine learning for 4.0 industry solutions; neural networks in chemistry and material characterization; ordinal classification; real world applications of BCI systems; and spiking neural networks: applications and algorithms.
Book Synopsis Recent Trends in Learning From Data by : Luca Oneto
Download or read book Recent Trends in Learning From Data written by Luca Oneto and published by Springer Nature. This book was released on 2020-04-03 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a timely snapshot and extensive practical and theoretical insights into the topic of learning from data. Based on the tutorials presented at the INNS Big Data and Deep Learning Conference, INNSBDDL2019, held on April 16-18, 2019, in Sestri Levante, Italy, the respective chapters cover advanced neural networks, deep architectures, and supervised and reinforcement machine learning models. They describe important theoretical concepts, presenting in detail all the necessary mathematical formalizations, and offer essential guidance on their use in current big data research.
Book Synopsis Some Properties of Empirical Risk Minimization Over Donsker Classes by :
Download or read book Some Properties of Empirical Risk Minimization Over Donsker Classes written by and published by . This book was released on 2005 with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt: We study properties of algorithms which minimize (or almost-minimise) empirical error over a Donsker class of functions. we show that the L2-diameter of the set of almost-minimizers is converging to zero in probability. Therefore, as the number of samples grows, it is becoming unlikely that adding a point (or a number of points) to the training set will result in a large jump (in L2 distance) to a new hypothesis. We also show that under some conditions the expected errors of the almost-minimizers are becoming close with a rate faster than pi(exp -1/2).
Book Synopsis Machine Learning and Knowledge Discovery in Databases: Research Track by : Danai Koutra
Download or read book Machine Learning and Knowledge Discovery in Databases: Research Track written by Danai Koutra and published by Springer Nature. This book was released on 2023-09-16 with total page 758 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Data Privacy Management, Cryptocurrencies and Blockchain Technology by : Joaquin Garcia-Alfaro
Download or read book Data Privacy Management, Cryptocurrencies and Blockchain Technology written by Joaquin Garcia-Alfaro and published by Springer Nature. This book was released on 2023-02-23 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings and revised selected papers from the ESORICS 2022 International Workshops on Data Privacy Management, Cryptocurrencies and Blockchain Technology, DPM 2022 and CBT 2022, which took place in Copenhagen, Denmark, during September 26–30, 2022. For DPM 2022, 10 full papers out of 21 submissions have been accepted for inclusion in this book. They were organized in topical sections as follows: differential privacy and data analysis; regulation, artificial intelligence, and formal verification; and leakage quantification and applications. The CBT 2022 workshop accepted 7 full papers and 3 short papers from 18 submissions. The papers were organized in the following topical sections: Bitcoin, lightning network and scalability; and anonymity, fault tolerance and governance; and short papers.
Book Synopsis Regularized Empirical Risk Minimization Under Missing Observations by : Andreas Luca Elsener
Download or read book Regularized Empirical Risk Minimization Under Missing Observations written by Andreas Luca Elsener and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Discrimination and Privacy in the Information Society by : Bart Custers
Download or read book Discrimination and Privacy in the Information Society written by Bart Custers and published by Springer Science & Business Media. This book was released on 2012-08-11 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: Vast amounts of data are nowadays collected, stored and processed, in an effort to assist in making a variety of administrative and governmental decisions. These innovative steps considerably improve the speed, effectiveness and quality of decisions. Analyses are increasingly performed by data mining and profiling technologies that statistically and automatically determine patterns and trends. However, when such practices lead to unwanted or unjustified selections, they may result in unacceptable forms of discrimination. Processing vast amounts of data may lead to situations in which data controllers know many of the characteristics, behaviors and whereabouts of people. In some cases, analysts might know more about individuals than these individuals know about themselves. Judging people by their digital identities sheds a different light on our views of privacy and data protection. This book discusses discrimination and privacy issues related to data mining and profiling practices. It provides technological and regulatory solutions, to problems which arise in these innovative contexts. The book explains that common measures for mitigating privacy and discrimination, such as access controls and anonymity, fail to properly resolve privacy and discrimination concerns. Therefore, new solutions, focusing on technology design, transparency and accountability are called for and set forth.
Book Synopsis Handbook of Trustworthy Federated Learning by : My T. Thai
Download or read book Handbook of Trustworthy Federated Learning written by My T. Thai and published by Springer Nature. This book was released on with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Handbook of Sharing Confidential Data by : Jörg Drechsler
Download or read book Handbook of Sharing Confidential Data written by Jörg Drechsler and published by CRC Press. This book was released on 2024-10-09 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical agencies, research organizations, companies, and other data stewards that seek to share data with the public face a challenging dilemma. They need to protect the privacy and confidentiality of data subjects and their attributes while providing data products that are useful for their intended purposes. In an age when information on data subjects is available from a wide range of data sources, as are the computational resources to obtain that information, this challenge is increasingly difficult. The Handbook of Sharing Confidential Data helps data stewards understand how tools from the data confidentiality literature—specifically, synthetic data, formal privacy, and secure computation—can be used to manage trade-offs in disclosure risk and data usefulness. Key features: • Provides overviews of the potential and the limitations of synthetic data, differential privacy, and secure computation • Offers an accessible review of methods for implementing differential privacy, both from methodological and practical perspectives • Presents perspectives from both computer science and statistical science for addressing data confidentiality and privacy • Describes genuine applications of synthetic data, formal privacy, and secure computation to help practitioners implement these approaches The handbook is accessible to both researchers and practitioners who work with confidential data. It requires familiarity with basic concepts from probability and data analysis.
Book Synopsis Mathematical Perspectives on Neural Networks by : Paul Smolensky
Download or read book Mathematical Perspectives on Neural Networks written by Paul Smolensky and published by Psychology Press. This book was released on 2013-05-13 with total page 865 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent years have seen an explosion of new mathematical results on learning and processing in neural networks. This body of results rests on a breadth of mathematical background which even few specialists possess. In a format intermediate between a textbook and a collection of research articles, this book has been assembled to present a sample of these results, and to fill in the necessary background, in such areas as computability theory, computational complexity theory, the theory of analog computation, stochastic processes, dynamical systems, control theory, time-series analysis, Bayesian analysis, regularization theory, information theory, computational learning theory, and mathematical statistics. Mathematical models of neural networks display an amazing richness and diversity. Neural networks can be formally modeled as computational systems, as physical or dynamical systems, and as statistical analyzers. Within each of these three broad perspectives, there are a number of particular approaches. For each of 16 particular mathematical perspectives on neural networks, the contributing authors provide introductions to the background mathematics, and address questions such as: * Exactly what mathematical systems are used to model neural networks from the given perspective? * What formal questions about neural networks can then be addressed? * What are typical results that can be obtained? and * What are the outstanding open problems? A distinctive feature of this volume is that for each perspective presented in one of the contributed chapters, the first editor has provided a moderately detailed summary of the formal results and the requisite mathematical concepts. These summaries are presented in four chapters that tie together the 16 contributed chapters: three develop a coherent view of the three general perspectives -- computational, dynamical, and statistical; the other assembles these three perspectives into a unified overview of the neural networks field.
Book Synopsis Mathematics for Machine Learning by : Marc Peter Deisenroth
Download or read book Mathematics for Machine Learning written by Marc Peter Deisenroth and published by Cambridge University Press. This book was released on 2020-04-23 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.
Author :United States. Congress. Senate. Committee on Energy and Natural Resources Publisher : ISBN 13 : Total Pages :344 pages Book Rating :4.0/5 ( download)
Book Synopsis Regulatory Fairness Act by : United States. Congress. Senate. Committee on Energy and Natural Resources
Download or read book Regulatory Fairness Act written by United States. Congress. Senate. Committee on Energy and Natural Resources and published by . This book was released on 1988 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Practical Fairness by : Aileen Nielsen
Download or read book Practical Fairness written by Aileen Nielsen and published by O'Reilly Media. This book was released on 2020-12-01 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fairness is an increasingly important topic as machine learning and AI more generally take over the world. While this is an active area of research, many realistic best practices are emerging at all steps along the data pipeline, from data selection and preprocessing to blackbox model audits. This book will guide you through the technical, legal, and ethical aspects of making your code fair and secure while highlighting cutting edge academic research and ongoing legal developments related to fairness and algorithms. There is mounting evidence that the widespread deployment of machine learning and artificial intelligence in business and government is reproducing the same biases we are trying to fight in the real world. For this reason, fairness is an increasingly important consideration for the data scientist. Yet discussions of what fairness means in terms of actual code are few and far between. This code will show you how to code fairly as well as cover basic concerns related to data security and privacy from a fairness perspective.
Book Synopsis The Law of Governance, Risk Management and Compliance by : Geoffrey P. Miller
Download or read book The Law of Governance, Risk Management and Compliance written by Geoffrey P. Miller and published by Aspen Publishing. This book was released on 2019-09-13 with total page 1243 pages. Available in PDF, EPUB and Kindle. Book excerpt: Geoffrey Miller’s The Law of Governance, Risk Management and Compliance is widely credited for introducing a new field of legal studies. Compliance and its related subjects of governance and risk management are major sources of jobs and also important developments in legal practice. The billions of dollars of fines paid over the past decade and the burgeoning and seemingly never-ending parade of compliance and risk management breakdowns – recently including the Wells Fargo sales practices scandal, the Volkswagen emissions cheat, and the Boeing 737 MAX crisis – all attest to the importance of the issues treated in this readable and timely book. New to the Third Edition: Comprehensive updates on recent developments New treatment of compliance failures: Wells Fargo account opening scandal, Volkswagen emissions cheat, important developments in Catholic Church sex abuse scandal. New treatment of risk management failures: the Boeing 737 MAX scandal. Professors and students will benefit from: Clear, concise definitions Fun and interesting problems Real-world perspective from an author who has been involved both as a scholar and as a member of a corporate board of directors Highly readable and interesting writing Text boxes containing key concepts and definitions Realistic problems for class discussion and analysis
Book Synopsis Fairness of CEO Compensation by : Mehtap Aldogan Eklund
Download or read book Fairness of CEO Compensation written by Mehtap Aldogan Eklund and published by Springer Nature. This book was released on 2019-12-05 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: Executive compensation and its fairness to stakeholders are topics of heated debate on platforms ranging from news forums to financial markets. This book stimulates critical thinking on executive compensation and guides academics and practitioners on the key concepts by developing a multi-faceted and multi-cultural framework. It also presents the new ‘Fair CEO Compensation,’ which uses a scientifically developed and structured stakeholder-based approach to reach optimal and fair CEO compensation, without capping bonuses or variable pay by rules and regulations. Financial, non-financial, organizational, strategic, cultural, personal, and social aspects are all taken into account in the framework. In addition to implementation guidelines and real-world examples, the book presents a checklist for businesses to measure the fairness of their CEO compensation based on the suggested framework. Moreover, the author also provides a survey template to help businesses investigate their employees’ perception of the fairness of their CEO’s compensation.
Download or read book Risk Management written by and published by . This book was released on 1980 with total page 788 pages. Available in PDF, EPUB and Kindle. Book excerpt:
