Gradient Expectations
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Author |
: Keith L. Downing |
Publisher |
: MIT Press |
Total Pages |
: 225 |
Release |
: 2023-07-18 |
ISBN-10 |
: 9780262374682 |
ISBN-13 |
: 0262374684 |
Rating |
: 4/5 (82 Downloads) |
Synopsis Gradient Expectations by : Keith L. Downing
An insightful investigation into the mechanisms underlying the predictive functions of neural networks—and their ability to chart a new path for AI. Prediction is a cognitive advantage like few others, inherently linked to our ability to survive and thrive. Our brains are awash in signals that embody prediction. Can we extend this capability more explicitly into synthetic neural networks to improve the function of AI and enhance its place in our world? Gradient Expectations is a bold effort by Keith L. Downing to map the origins and anatomy of natural and artificial neural networks to explore how, when designed as predictive modules, their components might serve as the basis for the simulated evolution of advanced neural network systems. Downing delves into the known neural architecture of the mammalian brain to illuminate the structure of predictive networks and determine more precisely how the ability to predict might have evolved from more primitive neural circuits. He then surveys past and present computational neural models that leverage predictive mechanisms with biological plausibility, identifying elements, such as gradients, that natural and artificial networks share. Behind well-founded predictions lie gradients, Downing finds, but of a different scope than those that belong to today’s deep learning. Digging into the connections between predictions and gradients, and their manifestation in the brain and neural networks, is one compelling example of how Downing enriches both our understanding of such relationships and their role in strengthening AI tools. Synthesizing critical research in neuroscience, cognitive science, and connectionism, Gradient Expectations offers unique depth and breadth of perspective on predictive neural-network models, including a grasp of predictive neural circuits that enables the integration of computational models of prediction with evolutionary algorithms.
Author |
: Andrea D. Sims |
Publisher |
: Cambridge University Press |
Total Pages |
: 333 |
Release |
: 2015-11-12 |
ISBN-10 |
: 9781316352038 |
ISBN-13 |
: 131635203X |
Rating |
: 4/5 (38 Downloads) |
Synopsis Inflectional Defectiveness by : Andrea D. Sims
Paradigmatic gaps ('missing' inflected forms) have traditionally been considered to be the random detritus of a language's history and marginal exceptions to the normal functioning of its inflectional system. Arguing that this is a misperception, Inflectional Defectiveness demonstrates that paradigmatic gaps are in fact normal and expected products of inflectional structure. Sims offers an accessible exploration of how and why inflectional defectiveness arises, why it persists, and how it is learned. The book presents a theory of morphology which is rooted in the implicative structure of the paradigm. This systematic exploration of the topic also addresses questions of inflection class organization, the morphology-syntax interface, the structure of the lexicon, and the nature of productivity. Presenting a novel synthesis of established research and new empirical data, this work is significant for researchers and graduate students in all fields of linguistics.
Author |
: Steve Sussman |
Publisher |
: Cambridge University Press |
Total Pages |
: 419 |
Release |
: 2017-02-06 |
ISBN-10 |
: 9781316943052 |
ISBN-13 |
: 1316943054 |
Rating |
: 4/5 (52 Downloads) |
Synopsis Substance and Behavioral Addictions by : Steve Sussman
Substance and Behavioral Addictions: Concepts, Causes, and Cures presents the concepts, etiology, assessment, prevention, and cessation of substance (tobacco, alcohol, other drugs, and food) and behavioral (gambling, Internet, shopping, love, sex, exercise, and work) addictions. The text provides a novel and integrative appetitive motivation framework of addiction, while acknowledging and referencing multi-level influences on addiction, such as neurobiological, cognitive, and micro-social and macro-social/physical environmental. The book discusses concurrent and substitute addiction, and offers prevention and treatment solutions, which are presented from a more integrative perspective than traditional presentations. This is an ideal text for upper-level undergraduates and graduate students, practitioners, and researchers.
Author |
: Merike Darmody |
Publisher |
: Taylor & Francis |
Total Pages |
: 187 |
Release |
: 2023-06-26 |
ISBN-10 |
: 9781000903256 |
ISBN-13 |
: 1000903257 |
Rating |
: 4/5 (56 Downloads) |
Synopsis Post-school Pathways of Migrant-Origin Youth in Europe by : Merike Darmody
This volume explores the role of structure and agency in shaping post-school pathways for migrant-origin young people, providing new insights from countries with different migration histories and transition systems. The book collates the work of leading international scholars to cover a number of jurisdictions across Europe, looking in depth at migrant transitions in different contexts. The chapters examine the influence of different education systems, migration status, race and ethnicity, social class, gender, and resilience on the success of transitions to higher education and the labour market. The book highlights the need for host countries to put in place comprehensive policies to counter ethnic inequalities and discrimination in their education and labour market systems while facilitating and supporting immigrant youth in pursuing their post-school pathways. This timely book will be of great interest to scholars, researchers, and postgraduate students in the fields of migration studies, sociology of education, and equity in education. Policymakers will find this book useful in informing policy development in education and the labour market.
Author |
: Kerrie L. Mengersen |
Publisher |
: Springer Nature |
Total Pages |
: 415 |
Release |
: 2020-05-28 |
ISBN-10 |
: 9783030425531 |
ISBN-13 |
: 3030425533 |
Rating |
: 4/5 (31 Downloads) |
Synopsis Case Studies in Applied Bayesian Data Science by : Kerrie L. Mengersen
Presenting a range of substantive applied problems within Bayesian Statistics along with their Bayesian solutions, this book arises from a research program at CIRM in France in the second semester of 2018, which supported Kerrie Mengersen as a visiting Jean-Morlet Chair and Pierre Pudlo as the local Research Professor. The field of Bayesian statistics has exploded over the past thirty years and is now an established field of research in mathematical statistics and computer science, a key component of data science, and an underpinning methodology in many domains of science, business and social science. Moreover, while remaining naturally entwined, the three arms of Bayesian statistics, namely modelling, computation and inference, have grown into independent research fields. While the research arms of Bayesian statistics continue to grow in many directions, they are harnessed when attention turns to solving substantive applied problems. Each such problem set has its own challenges and hence draws from the suite of research a bespoke solution. The book will be useful for both theoretical and applied statisticians, as well as practitioners, to inspect these solutions in the context of the problems, in order to draw further understanding, awareness and inspiration.
Author |
: Cheng Yong Tan |
Publisher |
: Springer Nature |
Total Pages |
: 84 |
Release |
: 2020-04-09 |
ISBN-10 |
: 9789811544910 |
ISBN-13 |
: 9811544913 |
Rating |
: 4/5 (10 Downloads) |
Synopsis Family Cultural Capital and Student Achievement by : Cheng Yong Tan
This book focuses on the relationship between cultural capital and student achievement. It fills the gap in the literature on large-scale quantitative studies of the effects of cultural capital. In particular, the review of empirical evidence presented, especially that from studies analyzing large-scale, international data from the Programme for International Student Assessment (PISA), makes a substantial contribution to the literature. This review addresses the knowledge gap on reviews investigating the effects of different forms of cultural capital on student achievement as compared to the more established evidence base in the related field of socioeconomic status.
Author |
: Ian David Lockhart Bogle |
Publisher |
: World Scientific |
Total Pages |
: 238 |
Release |
: 2006 |
ISBN-10 |
: 9789812772954 |
ISBN-13 |
: 9812772952 |
Rating |
: 4/5 (54 Downloads) |
Synopsis Computer Aided Methods in Optimal Design and Operations by : Ian David Lockhart Bogle
This book covers different topics on optimal design and operations with particular emphasis on chemical engineering applications. A wide range of optimization methods OCo deterministic, stochastic, global and hybrid OCo are considered. Containing papers presented at the bilateral workshop by British and Lithuanian scientists, the book brings together researchers'' contributions from different fields OCo chemical engineering including reaction and separation processes, food and biological production, as well as business cycle optimization, bankruptcy, protein analysis and bioinformatics. Sample Chapter(s). Chapter 1: Hybrid Methods for Optimisation (520 KB). Contents: Hybrid Methods for Optimisation (E S Fraga); An MILP Model for Multi-Class Data Classification (G Xu & L G Papageorgiou); Studying the Rate of Convergence of the Steepest Descent Optimisation Algorithm with Relaxation (R J Haycroft); Optimal Estimation of Parameters in Market Research Models (V Savani); A Redundancy Detection Approach to Mining Bioinformatics Data (H Camacho & A Salhi); Optimal Open-Loop Recipe Generation for Particle Size Distribution Control in Semi-Batch Emulsion Polymerisation (N Bianco & C D Immanuel); Multidimensional Scaling Using Parallel Genetic Algorithm (A Varoneckas et al.); Evaluating the Applicability of Time Temperature Integrators as Process Exploration and Validation Tools (S Bakalis et al.); Optimal Deflection Yoke Tuning (V Vaitkus et al.); and other papers. Readership: Academics, researchers, practitioners and postgraduates students in operations research and engineering."
Author |
: Alexey Piunovskiy |
Publisher |
: Springer Nature |
Total Pages |
: 356 |
Release |
: 2021-06-04 |
ISBN-10 |
: 9783030769284 |
ISBN-13 |
: 3030769283 |
Rating |
: 4/5 (84 Downloads) |
Synopsis Modern Trends in Controlled Stochastic Processes: by : Alexey Piunovskiy
This book presents state-of-the-art solution methods and applications of stochastic optimal control. It is a collection of extended papers discussed at the traditional Liverpool workshop on controlled stochastic processes with participants from both the east and the west. New problems are formulated, and progresses of ongoing research are reported. Topics covered in this book include theoretical results and numerical methods for Markov and semi-Markov decision processes, optimal stopping of Markov processes, stochastic games, problems with partial information, optimal filtering, robust control, Q-learning, and self-organizing algorithms. Real-life case studies and applications, e.g., queueing systems, forest management, control of water resources, marketing science, and healthcare, are presented. Scientific researchers and postgraduate students interested in stochastic optimal control,- as well as practitioners will find this book appealing and a valuable reference.
Author |
: Andrew Blake |
Publisher |
: MIT Press |
Total Pages |
: 472 |
Release |
: 2011-07-22 |
ISBN-10 |
: 9780262015776 |
ISBN-13 |
: 0262015773 |
Rating |
: 4/5 (76 Downloads) |
Synopsis Markov Random Fields for Vision and Image Processing by : Andrew Blake
State-of-the-art research on MRFs, successful MRF applications, and advanced topics for future study. This volume demonstrates the power of the Markov random field (MRF) in vision, treating the MRF both as a tool for modeling image data and, utilizing recently developed algorithms, as a means of making inferences about images. These inferences concern underlying image and scene structure as well as solutions to such problems as image reconstruction, image segmentation, 3D vision, and object labeling. It offers key findings and state-of-the-art research on both algorithms and applications. After an introduction to the fundamental concepts used in MRFs, the book reviews some of the main algorithms for performing inference with MRFs; presents successful applications of MRFs, including segmentation, super-resolution, and image restoration, along with a comparison of various optimization methods; discusses advanced algorithmic topics; addresses limitations of the strong locality assumptions in the MRFs discussed in earlier chapters; and showcases applications that use MRFs in more complex ways, as components in bigger systems or with multiterm energy functions. The book will be an essential guide to current research on these powerful mathematical tools.
Author |
: Richard S. Sutton |
Publisher |
: MIT Press |
Total Pages |
: 549 |
Release |
: 2018-11-13 |
ISBN-10 |
: 9780262039246 |
ISBN-13 |
: 0262039249 |
Rating |
: 4/5 (46 Downloads) |
Synopsis Reinforcement Learning, second edition by : Richard S. Sutton
The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.