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Efficient Sampling For Determinantal Point Processes
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Book Synopsis Determinantal Point Processes for Machine Learning by : Alex Kulesza
Download or read book Determinantal Point Processes for Machine Learning written by Alex Kulesza and published by Now Pub. This book was released on 2012-11-29 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph provides a comprehensible introduction to DPPs, focusing on the intuitions, algorithms, and extensions that are most relevant to the machine learning community.
Book Synopsis Information Processing in Medical Imaging by : Sebastien Ourselin
Download or read book Information Processing in Medical Imaging written by Sebastien Ourselin and published by Springer. This book was released on 2015-06-22 with total page 811 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 24th International Conference on Information Processing in Medical Imaging, IPMI 2015, held at the Sabhal Mor Ostaig College on the Isle of Skye, Scotland, UK, in June/July 2015. The 22 full papers and 41 poster papers presented in this volume were carefully reviewed and selected from 195 submissions. They were organized in topical sections named: probabilistic graphical models; MRI reconstruction; clustering; statistical methods; longitudinal analysis; microstructure imaging; shape analysis; multi-atlas fusion; fast image registration; deformation models; and the poster session.
Book Synopsis Zeros of Gaussian Analytic Functions and Determinantal Point Processes by : John Ben Hough
Download or read book Zeros of Gaussian Analytic Functions and Determinantal Point Processes written by John Ben Hough and published by American Mathematical Soc.. This book was released on 2009 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: Examines in some depth two important classes of point processes, determinantal processes and 'Gaussian zeros', i.e., zeros of random analytic functions with Gaussian coefficients. This title presents a primer on modern techniques on the interface of probability and analysis.
Book Synopsis Efficient Nonlinear Adaptive Filters by : Haiquan Zhao
Download or read book Efficient Nonlinear Adaptive Filters written by Haiquan Zhao and published by Springer Nature. This book was released on 2023-02-10 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the design, analysis, and application of nonlinear adaptive filters with the goal of improving efficient performance (ie the convergence speed, steady-state error, and computational complexity). The authors present a nonlinear adaptive filter, which is an important part of nonlinear system and digital signal processing and can be applied to diverse fields such as communications, control power system, radar sonar, etc. The authors also present an efficient nonlinear filter model and robust adaptive filtering algorithm based on the local cost function of optimal criterion to overcome non-Gaussian noise interference. The authors show how these achievements provide new theories and methods for robust adaptive filtering of nonlinear and non-Gaussian systems. The book is written for the scientist and engineer who are not necessarily an expert in the specific nonlinear filtering field but who want to learn about the current research and application. The book is also written to accompany a graduate/PhD course in the area of nonlinear system and adaptive signal processing.
Book Synopsis Sampling Techniques for Supervised or Unsupervised Tasks by : Frédéric Ros
Download or read book Sampling Techniques for Supervised or Unsupervised Tasks written by Frédéric Ros and published by Springer Nature. This book was released on 2019-10-26 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes in detail sampling techniques that can be used for unsupervised and supervised cases, with a focus on sampling techniques for machine learning algorithms. It covers theory and models of sampling methods for managing scalability and the “curse of dimensionality”, their implementations, evaluations, and applications. A large part of the book is dedicated to database comprising standard feature vectors, and a special section is reserved to the handling of more complex objects and dynamic scenarios. The book is ideal for anyone teaching or learning pattern recognition and interesting teaching or learning pattern recognition and is interested in the big data challenge. It provides an accessible introduction to the field and discusses the state of the art concerning sampling techniques for supervised and unsupervised task. Provides a comprehensive description of sampling techniques for unsupervised and supervised tasks; Describe implementation and evaluation of algorithms that simultaneously manage scalable problems and curse of dimensionality; Addresses the role of sampling in dynamic scenarios, sampling when dealing with complex objects, and new challenges arising from big data. "This book represents a timely collection of state-of-the art research of sampling techniques, suitable for anyone who wants to become more familiar with these helpful techniques for tackling the big data challenge." M. Emre Celebi, Ph.D., Professor and Chair, Department of Computer Science, University of Central Arkansas "In science the difficulty is not to have ideas, but it is to make them work" From Carlo Rovelli
Book Synopsis Perturbations, Optimization, and Statistics by : Tamir Hazan
Download or read book Perturbations, Optimization, and Statistics written by Tamir Hazan and published by MIT Press. This book was released on 2023-12-05 with total page 413 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Proceedings of the Forum "Math-for-Industry" 2018 by : Jin Cheng
Download or read book Proceedings of the Forum "Math-for-Industry" 2018 written by Jin Cheng and published by Springer Nature. This book was released on 2022-01-01 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume includes selected technical papers presented at the Forum “Math-for-Industry” 2018. The papers written by eminent researchers and academics working in the area of industrial mathematics from the viewpoint of financial mathematics, machine learning, neural networks, inverse problems, stochastic modelling, etc., discuss how the ingenuity of science, technology, engineering and mathematics are and will be expected to be utilized. This volume focuses on the role that mathematics-for-industry can play in interdisciplinary research to develop new methods. The contents are useful for researchers both in academia and industry working in interdisciplinary sectors.
Book Synopsis Computer Vision – ECCV 2020 by : Andrea Vedaldi
Download or read book Computer Vision – ECCV 2020 written by Andrea Vedaldi and published by Springer Nature. This book was released on 2020-11-04 with total page 861 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 30-volume set, comprising the LNCS books 12346 until 12375, constitutes the refereed proceedings of the 16th European Conference on Computer Vision, ECCV 2020, which was planned to be held in Glasgow, UK, during August 23-28, 2020. The conference was held virtually due to the COVID-19 pandemic. The 1360 revised papers presented in these proceedings were carefully reviewed and selected from a total of 5025 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.
Book Synopsis Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 by : Anne L. Martel
Download or read book Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 written by Anne L. Martel and published by Springer Nature. This book was released on 2020-10-02 with total page 842 pages. Available in PDF, EPUB and Kindle. Book excerpt: The seven-volume set LNCS 12261, 12262, 12263, 12264, 12265, 12266, and 12267 constitutes the refereed proceedings of the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, held in Lima, Peru, in October 2020. The conference was held virtually due to the COVID-19 pandemic. The 542 revised full papers presented were carefully reviewed and selected from 1809 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: machine learning methodologies Part II: image reconstruction; prediction and diagnosis; cross-domain methods and reconstruction; domain adaptation; machine learning applications; generative adversarial networks Part III: CAI applications; image registration; instrumentation and surgical phase detection; navigation and visualization; ultrasound imaging; video image analysis Part IV: segmentation; shape models and landmark detection Part V: biological, optical, microscopic imaging; cell segmentation and stain normalization; histopathology image analysis; opthalmology Part VI: angiography and vessel analysis; breast imaging; colonoscopy; dermatology; fetal imaging; heart and lung imaging; musculoskeletal imaging Part VI: brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; positron emission tomography
Book Synopsis Bioinformatics Research and Applications by : Yanjie Wei
Download or read book Bioinformatics Research and Applications written by Yanjie Wei and published by Springer Nature. This book was released on 2021-11-17 with total page 627 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 17th International Symposium on Bioinformatics Research and Applications, ISBRA 2021, held in Shenzhen, China, in November 2021. The 51 full papers presented in this book were carefully reviewed and selected from 135 submissions. They were organized in topical sections named: AI and disease; computational proteomics; biomedical imaging; drug screening and drug-drug interaction prediction; Biomedical data; sequencing data analysis.
Book Synopsis Sampling Methods by : Pascal Ardilly
Download or read book Sampling Methods written by Pascal Ardilly and published by Springer Science & Business Media. This book was released on 2006-02-08 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: Whenweagreedtoshareallofourpreparationofexercisesinsamplingtheory to create a book, we were not aware of the scope of the work. It was indeed necessary to compose the information, type out the compilations, standardise the notations and correct the drafts. It is fortunate that we have not yet measured the importance of this project, for this work probably would never have been attempted! In making available this collection of exercises, we hope to promote the teaching of sampling theory for which we wanted to emphasise its diversity. The exercises are at times purely theoretical while others are originally from real problems, enabling us to approach the sensitive matter of passing from theory to practice that so enriches survey statistics. The exercises that we present were used as educational material at the École Nationale de la Statistique et de l’Analyse de l’Information (ENSAI), where we had successively taught sampling theory. We are not the authors of all the exercises. In fact, some of them are due to Jean-Claude Deville and Laurent Wilms. We thank them for allowing us to reproduce their exercises. It is also possible that certain exercises had been initially conceived by an author that we have not identi?ed. Beyondthe contribution of our colleagues, and in all cases, we do not consider ourselves to be the lone authors of these exercises:they actually form part of a common heritagefrom ENSAI that has been enriched and improved due to questions from students and the work of all the demonstrators of the sampling course at ENSAI.
Book Synopsis Machine Learning and Knowledge Discovery in Databases by : Michele Berlingerio
Download or read book Machine Learning and Knowledge Discovery in Databases written by Michele Berlingerio and published by Springer. This book was released on 2019-01-22 with total page 883 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three volume proceedings LNAI 11051 – 11053 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2018, held in Dublin, Ireland, in September 2018. The total of 131 regular papers presented in part I and part II was carefully reviewed and selected from 535 submissions; there are 52 papers in the applied data science, nectar and demo track. The contributions were organized in topical sections named as follows: Part I: adversarial learning; anomaly and outlier detection; applications; classification; clustering and unsupervised learning; deep learningensemble methods; and evaluation. Part II: graphs; kernel methods; learning paradigms; matrix and tensor analysis; online and active learning; pattern and sequence mining; probabilistic models and statistical methods; recommender systems; and transfer learning. Part III: ADS data science applications; ADS e-commerce; ADS engineering and design; ADS financial and security; ADS health; ADS sensing and positioning; nectar track; and demo track.
Book Synopsis Mathematics and Computation by : Avi Wigderson
Download or read book Mathematics and Computation written by Avi Wigderson and published by Princeton University Press. This book was released on 2019-10-29 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the winner of the Turing Award and the Abel Prize, an introduction to computational complexity theory, its connections and interactions with mathematics, and its central role in the natural and social sciences, technology, and philosophy Mathematics and Computation provides a broad, conceptual overview of computational complexity theory—the mathematical study of efficient computation. With important practical applications to computer science and industry, computational complexity theory has evolved into a highly interdisciplinary field, with strong links to most mathematical areas and to a growing number of scientific endeavors. Avi Wigderson takes a sweeping survey of complexity theory, emphasizing the field’s insights and challenges. He explains the ideas and motivations leading to key models, notions, and results. In particular, he looks at algorithms and complexity, computations and proofs, randomness and interaction, quantum and arithmetic computation, and cryptography and learning, all as parts of a cohesive whole with numerous cross-influences. Wigderson illustrates the immense breadth of the field, its beauty and richness, and its diverse and growing interactions with other areas of mathematics. He ends with a comprehensive look at the theory of computation, its methodology and aspirations, and the unique and fundamental ways in which it has shaped and will further shape science, technology, and society. For further reading, an extensive bibliography is provided for all topics covered. Mathematics and Computation is useful for undergraduate and graduate students in mathematics, computer science, and related fields, as well as researchers and teachers in these fields. Many parts require little background, and serve as an invitation to newcomers seeking an introduction to the theory of computation. Comprehensive coverage of computational complexity theory, and beyond High-level, intuitive exposition, which brings conceptual clarity to this central and dynamic scientific discipline Historical accounts of the evolution and motivations of central concepts and models A broad view of the theory of computation's influence on science, technology, and society Extensive bibliography
Book Synopsis Computer Vision – ECCV 2018 by : Vittorio Ferrari
Download or read book Computer Vision – ECCV 2018 written by Vittorio Ferrari and published by Springer. This book was released on 2018-10-08 with total page 877 pages. Available in PDF, EPUB and Kindle. Book excerpt: The sixteen-volume set comprising the LNCS volumes 11205-11220 constitutes the refereed proceedings of the 15th European Conference on Computer Vision, ECCV 2018, held in Munich, Germany, in September 2018.The 776 revised papers presented were carefully reviewed and selected from 2439 submissions. The papers are organized in topical sections on learning for vision; computational photography; human analysis; human sensing; stereo and reconstruction; optimization; matching and recognition; video attention; and poster sessions.
Book Synopsis Statistical Inference and Simulation for Spatial Point Processes by : Jesper Moller
Download or read book Statistical Inference and Simulation for Spatial Point Processes written by Jesper Moller and published by CRC Press. This book was released on 2003-09-25 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spatial point processes play a fundamental role in spatial statistics and today they are an active area of research with many new applications. Although other published works address different aspects of spatial point processes, most of the classical literature deals only with nonparametric methods, and a thorough treatment of the theory and applications of simulation-based inference is difficult to find. Written by researchers at the top of the field, this book collects and unifies recent theoretical advances and examples of applications. The authors examine Markov chain Monte Carlo algorithms and explore one of the most important recent developments in MCMC: perfect simulation procedures.
Book Synopsis Neural Information Processing by : Tom Gedeon
Download or read book Neural Information Processing written by Tom Gedeon and published by Springer Nature. This book was released on 2019-12-10 with total page 662 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set of LNCS 11953, 11954, and 11955 constitutes the proceedings of the 26th International Conference on Neural Information Processing, ICONIP 2019, held in Sydney, Australia, in December 2019. The 173 full papers presented were carefully reviewed and selected from 645 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains. The third volume, LNCS 11955, is organized in topical sections on semantic and graph based approaches; spiking neuron and related models; text computing using neural techniques; time-series and related models; and unsupervised neural models.
Book Synopsis Machine Learning and Knowledge Discovery in Databases. Research Track by : Nuria Oliver
Download or read book Machine Learning and Knowledge Discovery in Databases. Research Track written by Nuria Oliver and published by Springer Nature. This book was released on 2021-09-09 with total page 817 pages. Available in PDF, EPUB and Kindle. Book excerpt: The multi-volume set LNAI 12975 until 12979 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2021, which was held during September 13-17, 2021. The conference was originally planned to take place in Bilbao, Spain, but changed to an online event due to the COVID-19 pandemic. The 210 full papers presented in these proceedings were carefully reviewed and selected from a total of 869 submissions. The volumes are organized in topical sections as follows: Research Track: Part I: Online learning; reinforcement learning; time series, streams, and sequence models; transfer and multi-task learning; semi-supervised and few-shot learning; learning algorithms and applications. Part II: Generative models; algorithms and learning theory; graphs and networks; interpretation, explainability, transparency, safety. Part III: Generative models; search and optimization; supervised learning; text mining and natural language processing; image processing, computer vision and visual analytics. Applied Data Science Track: Part IV: Anomaly detection and malware; spatio-temporal data; e-commerce and finance; healthcare and medical applications (including Covid); mobility and transportation. Part V: Automating machine learning, optimization, and feature engineering; machine learning based simulations and knowledge discovery; recommender systems and behavior modeling; natural language processing; remote sensing, image and video processing; social media.
