Metric Learning

Author: Aurelien Bellet,Amaury Habrard,Marc Sebban

Publisher: Morgan & Claypool Publishers

ISBN: 1627053662

Category: Computers

Page: 151

View: 4171

Similarity between objects plays an important role in both human cognitive processes and artificial systems for recognition and categorization. How to appropriately measure such similarities for a given task is crucial to the performance of many machine learning, pattern recognition and data mining methods. This book is devoted to metric learning, a set of techniques to automatically learn similarity and distance functions from data that has attracted a lot of interest in machine learning and related fields in the past ten years. In this book, we provide a thorough review of the metric learning literature that covers algorithms, theory and applications for both numerical and structured data. We first introduce relevant definitions and classic metric functions, as well as examples of their use in machine learning and data mining. We then review a wide range of metric learning algorithms, starting with the simple setting of linear distance and similarity learning. We show how one may scale-up these methods to very large amounts of training data. To go beyond the linear case, we discuss methods that learn nonlinear metrics or multiple linear metrics throughout the feature space, and review methods for more complex settings such as multi-task and semi-supervised learning. Although most of the existing work has focused on numerical data, we cover the literature on metric learning for structured data like strings, trees, graphs and time series. In the more technical part of the book, we present some recent statistical frameworks for analyzing the generalization performance in metric learning and derive results for some of the algorithms presented earlier. Finally, we illustrate the relevance of metric learning in real-world problems through a series of successful applications to computer vision, bioinformatics and information retrieval.

Metric Learning

A Review

Author: Brian Kulis

Publisher: Now Pub

ISBN: 9781601986962

Category: Computers

Page: 92

View: 7133

Metric Learning: A Review presents an overview of existing research in metric learning, including recent progress on scaling to high-dimensional feature spaces and to data sets with an extremely large number of data points. It presents as unified a framework as possible under which existing research on metric learning can be cast.

Discriminative Learning in Biometrics

Author: David Zhang,Yong Xu,Wangmeng Zuo

Publisher: Springer

ISBN: 9811020566

Category: Computers

Page: 266

View: 6573

This monograph describes the latest advances in discriminative learning methods for biometric recognition. Specifically, it focuses on three representative categories of methods: sparse representation-based classification, metric learning, and discriminative feature representation, together with their applications in palmprint authentication, face recognition and multi-biometrics. The ideas, algorithms, experimental evaluation and underlying rationales are also provided for a better understanding of these methods. Lastly, it discusses several promising research directions in the field of discriminative biometric recognition.

Sparse Representation, Modeling and Learning in Visual Recognition

Theory, Algorithms and Applications

Author: Hong Cheng

Publisher: Springer

ISBN: 1447167147

Category: Computers

Page: 257

View: 2981

This unique text/reference presents a comprehensive review of the state of the art in sparse representations, modeling and learning. The book examines both the theoretical foundations and details of algorithm implementation, highlighting the practical application of compressed sensing research in visual recognition and computer vision. Topics and features: describes sparse recovery approaches, robust and efficient sparse representation, and large-scale visual recognition; covers feature representation and learning, sparsity induced similarity, and sparse representation and learning-based classifiers; discusses low-rank matrix approximation, graphical models in compressed sensing, collaborative representation-based classification, and high-dimensional nonlinear learning; includes appendices outlining additional computer programming resources, and explaining the essential mathematics required to understand the book.

Machine Learning and Knowledge Discovery in Databases

European Conference, ECML PKDD 2012, Bristol, UK, September 24-28, 2012. Proceedings

Author: Peter A. Flach,Tijl De Bie,Nello Cristianini

Publisher: Springer

ISBN: 3642334601

Category: Computers

Page: 879

View: 8458

This two-volume set LNAI 7523 and LNAI 7524 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2012, held in Bristol, UK, in September 2012. The 105 revised research papers presented together with 5 invited talks were carefully reviewed and selected from 443 submissions. The final sections of the proceedings are devoted to Demo and Nectar papers. The Demo track includes 10 papers (from 19 submissions) and the Nectar track includes 4 papers (from 14 submissions). The papers grouped in topical sections on association rules and frequent patterns; Bayesian learning and graphical models; classification; dimensionality reduction, feature selection and extraction; distance-based methods and kernels; ensemble methods; graph and tree mining; large-scale, distributed and parallel mining and learning; multi-relational mining and learning; multi-task learning; natural language processing; online learning and data streams; privacy and security; rankings and recommendations; reinforcement learning and planning; rule mining and subgroup discovery; semi-supervised and transductive learning; sensor data; sequence and string mining; social network mining; spatial and geographical data mining; statistical methods and evaluation; time series and temporal data mining; and transfer learning.

Machine Learning and Knowledge Discovery in Databases

European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings

Author: Annalisa Appice,Pedro Pereira Rodrigues,Vítor Santos Costa,Carlos Soares,João Gama,Alípio Jorge

Publisher: Springer

ISBN: 3319235281

Category: Computers

Page: 709

View: 2684

The three volume set LNAI 9284, 9285, and 9286 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2015, held in Porto, Portugal, in September 2015. The 131 papers presented in these proceedings were carefully reviewed and selected from a total of 483 submissions. These include 89 research papers, 11 industrial papers, 14 nectar papers, and 17 demo papers. They were organized in topical sections named: classification, regression and supervised learning; clustering and unsupervised learning; data preprocessing; data streams and online learning; deep learning; distance and metric learning; large scale learning and big data; matrix and tensor analysis; pattern and sequence mining; preference learning and label ranking; probabilistic, statistical, and graphical approaches; rich data; and social and graphs. Part III is structured in industrial track, nectar track, and demo track.

Data Classification

Algorithms and Applications

Author: Charu C. Aggarwal

Publisher: CRC Press

ISBN: 1466586753

Category: Business & Economics

Page: 707

View: 8040

Comprehensive Coverage of the Entire Area of Classification Research on the problem of classification tends to be fragmented across such areas as pattern recognition, database, data mining, and machine learning. Addressing the work of these different communities in a unified way, Data Classification: Algorithms and Applications explores the underlying algorithms of classification as well as applications of classification in a variety of problem domains, including text, multimedia, social network, and biological data. This comprehensive book focuses on three primary aspects of data classification: Methods: The book first describes common techniques used for classification, including probabilistic methods, decision trees, rule-based methods, instance-based methods, support vector machine methods, and neural networks. Domains: The book then examines specific methods used for data domains such as multimedia, text, time-series, network, discrete sequence, and uncertain data. It also covers large data sets and data streams due to the recent importance of the big data paradigm. Variations: The book concludes with insight on variations of the classification process. It discusses ensembles, rare-class learning, distance function learning, active learning, visual learning, transfer learning, and semi-supervised learning as well as evaluation aspects of classifiers.

Neural Information Processing

16th International Conference, ICONIP 2009, Bangkok, Thailand, December 1-5, 2009, Proceedings

Author: Chi-Sing Leung,Minho Lee,Jonathan H. Chan

Publisher: Springer Science & Business Media

ISBN: 364210682X

Category: Computers

Page: 888

View: 5443

The two volumes LNCS 5863 and 5864 constitute the proceedings of the 16th International Conference on Neural Information Processing, ICONIP 2009, held in Bangkok, Thailand, in December 2009. The 145 regular session papers and 53 special session papers presented were carefully reviewed and selected from 466 submissions. The papers are structured in topical sections on cognitive science and computational neuroscience, neurodynamics, mathematical modeling and analysis, kernel and related methods, learning algorithms, pattern analysis, face analysis and processing, image processing, financial applications, computer vision, control and robotics, evolutionary computation, other emerging computational methods, signal, data and text processing, artificial spiking neural systems: nonlinear dynamics and engineering applications, towards brain-inspired systems, computational advances in bioinformatics, data mining for cybersecurity, evolutionary neural networks: theory and practice, hybrid and adaptive systems for computer vision and robot control, intelligent data mining, neural networks for data mining, and SOM and related subjects and its applications.

Intelligent Computing in Bioinformatics

10th International Conference, ICIC 2014, Taiyuan, China, August 3-6, 2014, Proceedings

Author: De-Shuang Huang,Kyungsook Han,Michael Gromiha

Publisher: Springer

ISBN: 3319093304

Category: Computers

Page: 510

View: 3727

This book – in conjunction with the volumes LNCS 8588 and LNAI 8589 – constitutes the refereed proceedings of the 10th International Conference on Intelligent Computing, ICIC 2014, held in Taiyuan, China, in August 2014. The 58 papers of this volume were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections such as machine learning; neural networks; image processing; computational systems biology and medical informatics; biomedical informatics theory and methods; advances on bio-inspired computing; protein and gene bioinformatics: analysis, algorithms, applications.

Neural Information Processing

20th International Conference, ICONIP 2013, Daegu, Korea, November 3-7, 2013. Proceedings

Author: Minho Lee,Akira Hirose,Zeng-Guang Hou,Rhee Man Kil

Publisher: Springer

ISBN: 3642420516

Category: Computers

Page: 638

View: 4649

The three volume set LNCS 8226, LNCS 8227, and LNCS 8228 constitutes the proceedings of the 20th International Conference on Neural Information Processing, ICONIP 2013, held in Daegu, Korea, in November 2013. The 180 full and 75 poster papers presented together with 4 extended abstracts were carefully reviewed and selected from numerous submissions. These papers cover all major topics of theoretical research, empirical study and applications of neural information processing research. The specific topics covered are as follows: cognitive science and artificial intelligence; learning theory, algorithms and architectures; computational neuroscience and brain imaging; vision, speech and signal processing; control, robotics and hardware technologies and novel approaches and applications.

Machine Learning in Medical Imaging

First International Workshop, MLMI 2010, Held in Conjunction with MICCAI 2010, Beijing, China, September 20, 2010, Proceedings

Author: Fei Wang,Pingkun Yan,Kenji Suzuki,Dinggang Shen

Publisher: Springer Science & Business Media

ISBN: 3642159478

Category: Computers

Page: 192

View: 6113

This book constitutes the refereed proceedings of the First International Workshop on Machine Learning in Medical Imaging, MLMI 2010, held in conjunction with MICCAI 2010, in Beijing, China, in September 2010. The 23 revised full papers presented were carefully reviewed and selected from 38 submissions. The papers address topics such as machine learning applications to medical images, medical image analysis, multi-modality fusion, image reconstruction for medical imaging, computer-aided detection/diagnosis, medical image retrieval, cellular image analysis, molecular/pathologic image analysis, and dynamic, functional, physiologic, and anatomic imaging.

Person Re-Identification

Author: Shaogang Gong,Marco Cristani,Shuicheng Yan,Chen Change Loy

Publisher: Springer Science & Business Media

ISBN: 144716296X

Category: Computers

Page: 445

View: 8136

The first book of its kind dedicated to the challenge of person re-identification, this text provides an in-depth, multidisciplinary discussion of recent developments and state-of-the-art methods. Features: introduces examples of robust feature representations, reviews salient feature weighting and selection mechanisms and examines the benefits of semantic attributes; describes how to segregate meaningful body parts from background clutter; examines the use of 3D depth images and contextual constraints derived from the visual appearance of a group; reviews approaches to feature transfer function and distance metric learning and discusses potential solutions to issues of data scalability and identity inference; investigates the limitations of existing benchmark datasets, presents strategies for camera topology inference and describes techniques for improving post-rank search efficiency; explores the design rationale and implementation considerations of building a practical re-identification system.

Emerging Trends in Visual Computing

LIX Fall Colloquium, ETVC 2008, Palaiseau, France, November 18-20, 2008, Revised Selected and Invited Papers

Author: Frank Nielsen

Publisher: Springer Science & Business Media

ISBN: 3642008259

Category: Computers

Page: 386

View: 6229

This book is an outcome of the LIX Fall Colloquium on the Emerging Trends in Visual Computing, ETVC 2008, which was held in Palaiseau, France, November 18-20, 2008. During the event, 25 renowned invited speakers gave lectures on their areas of expertise within the field of visual computing. From these talks, a total of 15 state-of-the-art articles have been assembled in this volume. All articles were thoroughly reviewed and improved, according to the suggestions of the referees. The 15 contributions presented in this state-of-the-art survey are organized in topical sections on: geometric computing, information geometry and applications, computer graphics and vision, information retrieval, and medical imaging and computational anatomy. They are preceded by the abstracts of the talks given at ETVC 2008.

Emerging Technologies for Information Systems, Computing, and Management

Author: W. Eric Wong,Tinghuai Ma

Publisher: Springer Science & Business Media

ISBN: 1461470102

Category: Technology & Engineering

Page: 1339

View: 357

This book aims to examine innovation in the fields of information technology, software engineering, industrial engineering, management engineering. Topics covered in this publication include; Information System Security, Privacy, Quality Assurance, High-Performance Computing and Information System Management and Integration. The book presents papers from The Second International Conference for Emerging Technologies Information Systems, Computing, and Management (ICM2012) which was held on December 1 to 2, 2012 in Hangzhou, China.