Machine Theory

Spin glass models were introduced by physicists in the 1970s to model the statistical properties of certain magnetic materials. Over the last half century, these models have motivated a blossoming line of mathematical work with applications to multiple...

Probably almost correct (PAC) bounds have been an intensive field of research over the last two decades. Hundreds of papers have been published and much progress has been made resulting in PAC-Bayes bounds becoming an important technique in machine...

Reinforcement learning agents have demonstrated remarkable achievements in simulated environments. Data efficiency, however, significantly impedes carrying this success over to real environments. The design of data-efficient agents that address this...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9781638282082Author Brandon AmosFormat PaperbackPage Count 156Imprint now publishers IncPublisher now publishers IncWeight(grams) 230g

Deep learning (DL) has proven to be a highly effective approach for developing models in diverse contexts, including visual perception, speech recognition, and machine translation. Automated deep learning (AutoDL) endeavors to minimize the need for human...

This book is designed as a reference text and provides a comprehensive overview of conceptual and practical knowledge about deep learning in medical image processing techniques. The post-pandemic situation teaches us the importance of doctors, medical...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9789815079203Author Basant VermaFormat PaperbackPage Count 240Imprint Bentham Science PublishersPublisher Bentham Science PublishersWeight(grams) 585g

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9783903331174Author Steven CooperFormat PaperbackPage Count 182Imprint Data SciencePublisher Data ScienceWeight(grams) 204gDimensions(mm) 203mm * 127mm * 11mm

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9781913397043Author Genics TrustFormat PaperbackPage Count 194Imprint Thomas William SwainPublisher Thomas William SwainWeight(grams) 290gDimensions(mm)...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9781681088556Author Osondu OguikeFormat PaperbackPage Count 344Imprint Bentham Science PublishersPublisher Bentham Science PublishersWeight(grams) 178g

Non-convex Optimization for Machine Learning takes an in-depth look at the basics of non-convex optimization with applications to machine learning. It introduces the rich literature in this area, as well as equips the reader with the tools and techniques...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9781647483197Author Herbert JonesFormat HardbackPage Count 182Imprint Bravex PublicationsPublisher Bravex PublicationsWeight(grams) 612gDimensions(mm) 254mm...

Multi-armed bandits is a rich, multi-disciplinary area that has been studied since 1933, with a surge of activity in the past 10-15 years. This is the first monograph to provide a textbook like treatment of the subject.The work on multi-armed bandits can...

Provides a tutorial overview of several foundational methods for dimension reduction. The authors divide the methods into projective methods and methods that model the manifold on which the data lies. For projective methods, they review projection...

Determinantal point processes (DPPs) are elegant probabilistic models of repulsion that arise in quantum physics and random matrix theory. In contrast to traditional structured models like Markov random fields, which become intractable and hard to...

Deep learning has become the dominant approach in addressing various tasks in Natural Language Processing (NLP). Although text inputs are typically represented as a sequence of tokens, there is a rich variety of NLP problems that can be best expressed...

The two-volume set LNCS 14634 and 14635 constitutes the refereed proceedings of the 27th European Conference on Applications of Evolutionary Computation, EvoApplications 2024, held as part of EvoStar 2024, in Aberystwyth, UK, April 3–5, 2024, and...

Many modern methods for prediction leverage nearest neighbour search to find past training examples most similar to a test example, an idea that dates back in text to at least the 11th century and has stood the test of time. This monograph explains the...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9783903331563Author Steven CooperFormat HardbackPage Count 182Imprint Data SciencePublisher Data ScienceWeight(grams) 327gDimensions(mm) 203mm * 127mm * 14mm

This monograph builds on Tensor Networks for Dimensionality Reduction and Large-scale Optimization: Part 1 Low-Rank Tensor Decompositions by discussing tensor network models for super-compressed higher-order representation of data/parameters and cost...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9781680837889Author Peter KairouzFormat PaperbackPage Count 224Imprint now publishers IncPublisher now publishers IncWeight(grams) 322g

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9781601985583Author Mauricio A. AlvarezFormat PaperbackPage Count 86Imprint now publishers IncPublisher now publishers IncWeight(grams) 135gDimensions(mm)...

Monte Carlo methods, in particular those based on Markov chains and on interacting particle systems, are by now tools that are routinely used in machine learning. These methods have had a profound impact on statistical inference in a wide range of...

Over the last decade, the long-running endeavour to automate high-level processes in machine learning (ML) has risen to mainstream prominence. Beyond this, an even loftier goal is the pursuit of autonomy, which describes the capability of the system to...

Regression analysis is a key area of interest in the field of data analysis and machine learning which is devoted to exploring the dependencies between variables, often using vectors. The emergence of high dimensional data in technologies such as...

Can machine learning deliver AI? Theoretical results, inspiration from the brain and cognition, as well as machine learning experiments suggest that in order to learn the kind of complicated functions that can represent high-level abstractions (e.g. in...

Networks are ubiquitous in science and have become a focal point for discussion in everyday life. Formal statistical models for the analysis of network data have emerged as a major topic of interest in diverse areas of study, and most of these involve a...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9781805451303Author Vinay KumarFormat PaperbackPage Count 172Imprint Independent AuthorPublisher Independent AuthorWeight(grams) 236g

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9789732348079Author Alanna MaldonadoFormat PaperbackPage Count 76Imprint Alanna MaldonadoPublisher Alanna MaldonadoWeight(grams) 154g

The metric learning problem is concerned with learning a distance function tuned to a particular task, and has been shown to be useful when used in conjunction with nearest-neighbor methods and other techniques that rely on distances or similarities...

Automated theorem proving represents a significant and long-standing area of research in computer science, with numerous applications. A large proportion of the methods developed to date for the implementation of automated theorem provers (ATPs) have...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9783988313683Author Carl DennisFormat PaperbackPage Count 102Imprint Carl DennisPublisher Carl DennisWeight(grams) 145g

Variational autoencoders (VAEs) are powerful deep generative models widely used to represent high-dimensional complex data through a low-dimensional latent space learned in an unsupervised manner. In this monograph the authors introduce and discuss a...

This monograph reviews a class of univariate piecewise polynomial functions known as discrete splines, which share properties analogous to the better-known class of spline functions, but where continuity in derivatives is replaced by continuity in...

Many problems of recent interest in statistics and machine learning can be posed in the framework of convex optimization. Due to the explosion in size and complexity of modern datasets, it is increasingly important to be able to solve problems with a...

Online auctions are one of the most fundamental facets of the modern economy and power an industry generating hundreds of billions of dollars a year in revenue. Online auction theory has historically focused on the question of designing the best way to...

Sequential decision making, commonly formalized as Markov Decision Process (MDP) optimization, is an important challenge in artificial intelligence. Two key approaches to this problem are reinforcement learning (RL) and planning. This monograph surveys...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9798889950561Author SundraramankFormat PaperbackPage Count 228Imprint Self PublisherPublisher Self PublisherWeight(grams) 308g

The authors of this monograph survey recent progress in using spectral methods including matrix and tensor decomposition techniques to learn many popular latent variable models. With careful implementation, tensor-based methods can run efficiently in...

In contemporary science and engineering applications, the volume of available data is growing at an enormous rate. Spectral methods have emerged as a simple yet surprisingly effective approach for extracting information from massive, noisy and incomplete...