Author: Jun Zhu
Publisher:
ISBN:
Category : Entropy (Information theory)
Languages : en
Pages : 27
Get Book Here
Book Description
Abstract: "Standard max-margin structured prediction methods concentrate directly on the input-output mapping, and the lack of an elegant probabilistic interpretation causes limitations. In this paper, we present a novel framework called Maximum Entropy Discrimination Markov Networks (MaxEntNet) to do Bayesian max-margin structured learning by using expected margin constraints to define a feasible distribution subspace and applying the maximum entropy principle to choose the best distribution from this subspace. We show that MaxEntNet subsumes the standard max-margin Markov networks (M3N) as a spacial case where the predictive model is assumed to be linear and the parameter prior is a standard normal. Based on this understanding, we propose the Laplace max-margin Markov networks (LapM3N) which use the Laplace prior instead of the standard normal. We show that the adoption of a Laplace prior of the parameter makes LapM3N enjoy properties expected from a sparsified M3N. Unlike the L1-regularized maximum likelihood estimation which sets small weights to zeros to achieve sparsity, LapM3N posteriorly weights the parameters and features with smaller weights are shrunk more. This posterior weighting effect makes LapM3N more stable with respect to the magnitudes of the regularization coefficients and more generalizable. To learn a LapM3N, we present an efficient iterative learning algorithm based on variational approximation and existing convex optimization methods employed in M3N. The feasibility and promise of LapM3N are demonstrated on both synthetic and real OCR data sets.
Author:
Publisher: ScholarlyEditions
ISBN: 1464920877
Category : Computers
Languages : en
Pages : 935
Get Book Here
Book Description
Advances in Machine Learning Research and Application: 2011 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about Machine Learning. The editors have built Advances in Machine Learning Research and Application: 2011 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Machine Learning in this eBook to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Advances in Machine Learning Research and Application: 2011 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.
Author: Tony Jebara
Publisher: Springer Science & Business Media
ISBN: 1441990119
Category : Computers
Languages : en
Pages : 213
Get Book Here
Book Description
Machine Learning: Discriminative and Generative covers the main contemporary themes and tools in machine learning ranging from Bayesian probabilistic models to discriminative support-vector machines. However, unlike previous books that only discuss these rather different approaches in isolation, it bridges the two schools of thought together within a common framework, elegantly connecting their various theories and making one common big-picture. Also, this bridge brings forth new hybrid discriminative-generative tools that combine the strengths of both camps. This book serves multiple purposes as well. The framework acts as a scientific breakthrough, fusing the areas of generative and discriminative learning and will be of interest to many researchers. However, as a conceptual breakthrough, this common framework unifies many previously unrelated tools and techniques and makes them understandable to a larger portion of the public. This gives the more practical-minded engineer, student and the industrial public an easy-access and more sensible road map into the world of machine learning. Machine Learning: Discriminative and Generative is designed for an audience composed of researchers & practitioners in industry and academia. The book is also suitable as a secondary text for graduate-level students in computer science and engineering.
Author: Edoardo M. Airoldi
Publisher: CRC Press
ISBN: 1466504080
Category : Computers
Languages : en
Pages : 622
Get Book Here
Book Description
In response to scientific needs for more diverse and structured explanations of statistical data, researchers have discovered how to model individual data points as belonging to multiple groups. Handbook of Mixed Membership Models and Their Applications shows you how to use these flexible modeling tools to uncover hidden patterns in modern high-dimensional multivariate data. It explores the use of the models in various application settings, including survey data, population genetics, text analysis, image processing and annotation, and molecular biology. Through examples using real data sets, you’ll discover how to characterize complex multivariate data in: Studies involving genetic databases Patterns in the progression of diseases and disabilities Combinations of topics covered by text documents Political ideology or electorate voting patterns Heterogeneous relationships in networks, and much more The handbook spans more than 20 years of the editors’ and contributors’ statistical work in the field. Top researchers compare partial and mixed membership models, explain how to interpret mixed membership, delve into factor analysis, and describe nonparametric mixed membership models. They also present extensions of the mixed membership model for text analysis, sequence and rank data, and network data as well as semi-supervised mixed membership models.
Author: Tiziano Squartini
Publisher:
ISBN: 9783319694375
Category : Engineering
Languages : en
Pages : 116
Get Book Here
Book Description
Author: Davide Ciucci
Publisher: Springer
ISBN: 3642412181
Category : Computers
Languages : en
Pages : 412
Get Book Here
Book Description
This book constitutes the thoroughly refereed conference proceedings of the 14th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, RSFDGrC 2013, held in Halifax, Canada in October 2013 as one of the co-located conference of the 2013 Joint Rough Set Symposium, JRS 2013. The 69 papers (including 44 regular and 25 short papers) included in the JRS proceedings (LNCS 8170 and LNCS 8171) were carefully reviewed and selected from 106 submissions. The papers in this volume cover topics such as inconsistency, incompleteness, non-determinism; fuzzy and rough hybridization; granular computing and covering-based rough sets; soft clustering; image and medical data analysis.
Author: Paulo S.R. Diniz
Publisher: Academic Press
ISBN: 0123972264
Category : Technology & Engineering
Languages : en
Pages : 1559
Get Book Here
Book Description
This first volume, edited and authored by world leading experts, gives a review of the principles, methods and techniques of important and emerging research topics and technologies in machine learning and advanced signal processing theory. With this reference source you will: Quickly grasp a new area of research Understand the underlying principles of a topic and its application Ascertain how a topic relates to other areas and learn of the research issues yet to be resolved Quick tutorial reviews of important and emerging topics of research in machine learning Presents core principles in signal processing theory and shows their applications Reference content on core principles, technologies, algorithms and applications Comprehensive references to journal articles and other literature on which to build further, more specific and detailed knowledge Edited by leading people in the field who, through their reputation, have been able to commission experts to write on a particular topic
Author: Balaji Krishnapuram
Publisher: CRC Press
ISBN: 143983928X
Category : Computers
Languages : en
Pages : 316
Get Book Here
Book Description
In machine learning applications, practitioners must take into account the cost associated with the algorithm. These costs include: Cost of acquiring training dataCost of data annotation/labeling and cleaningComputational cost for model fitting, validation, and testingCost of collecting features/attributes for test dataCost of user feedback collect
Author: Qiang Yang
Publisher: Springer
ISBN: 3030161420
Category : Computers
Languages : en
Pages : 575
Get Book Here
Book Description
The three-volume set LNAI 11439, 11440, and 11441 constitutes the thoroughly refereed proceedings of the 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2019, held in Macau, China, in April 2019. The 137 full papers presented were carefully reviewed and selected from 542 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, visualization, decision-making systems, and the emerging applications. They are organized in the following topical sections: classification and supervised learning; text and opinion mining; spatio-temporal and stream data mining; factor and tensor analysis; healthcare, bioinformatics and related topics; clustering and anomaly detection; deep learning models and applications; sequential pattern mining; weakly supervised learning; recommender system; social network and graph mining; data pre-processing and featureselection; representation learning and embedding; mining unstructured and semi-structured data; behavioral data mining; visual data mining; and knowledge graph and interpretable data mining.
Author: Jianrong Tan
Publisher: Springer
ISBN: 9811065535
Category : Technology & Engineering
Languages : en
Pages : 1667
Get Book Here
Book Description
Focusing on innovation, these proceedings present recent advances in the field of mechanical design in China and offer researchers, scholars and scientists an international platform to present their research findings and exchange their ideas. In the context of the “Made in China 2025” development strategy, one central aspect of the ICMD2017 was Innovative Design Pushes “Made in China 2025.” The book highlights research hotspots in mechanical design, such as design methodology, green design, robotics and mechanics, and reliability design, while also combining industrial design and mechanical design.
