Feature Aware Label Space Dimension Reduction For Multi Label Classification Problem

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Neural Information Processing

Author : Tom Gedeon
Publisher : Springer Nature
ISBN 13 : 3030368025
Total Pages : 802 pages
Book Rating : 4.0/5 (33 download)

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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 2019-12-05 with total page 802 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set CCIS 1142 and 1143 constitutes thoroughly refereed contributions presented at the 26th International Conference on Neural Information Processing, ICONIP 2019, held in Sydney, Australia, in December 2019. For ICONIP 2019 a total of 345 papers was carefully reviewed and selected for publication out of 645 submissions. The 168 papers included in this volume set were organized in topical sections as follows: adversarial networks and learning; convolutional neural networks; deep neural networks; embeddings and feature fusion; human centred computing; human centred computing and medicine; human centred computing for emotion; hybrid models; image processing by neural techniques; learning from incomplete data; model compression and optimization; neural network applications; neural network models; semantic and graph based approaches; social network computing; spiking neuron and related models; text computing using neural techniques; time-series and related models; and unsupervised neural models.

Neural Information Processing

Author : Biao Luo
Publisher : Springer Nature
ISBN 13 : 9819980739
Total Pages : 621 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Neural Information Processing by : Biao Luo

Download or read book Neural Information Processing written by Biao Luo and published by Springer Nature. This book was released on 2023-11-14 with total page 621 pages. Available in PDF, EPUB and Kindle. Book excerpt: The six-volume set LNCS 14447 until 14452 constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 652 papers presented in the proceedings set were carefully reviewed and selected from 1274 submissions. They focus on theory and algorithms, cognitive neurosciences; human centred computing; applications in neuroscience, neural networks, deep learning, and related fields.

Computer Vision – ECCV 2020

Author : Andrea Vedaldi
Publisher : Springer Nature
ISBN 13 : 303058545X
Total Pages : 861 pages
Book Rating : 4.0/5 (35 download)

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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.

Neural Information Processing

Author : Akira Hirose
Publisher : Springer
ISBN 13 : 3319466755
Total Pages : 661 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Neural Information Processing by : Akira Hirose

Download or read book Neural Information Processing written by Akira Hirose and published by Springer. This book was released on 2016-09-30 with total page 661 pages. Available in PDF, EPUB and Kindle. Book excerpt: The four volume set LNCS 9947, LNCS 9948, LNCS 9949, and LNCS 9950 constitues the proceedings of the 23rd International Conference on Neural Information Processing, ICONIP 2016, held in Kyoto, Japan, in October 2016. The 296 full papers presented were carefully reviewed and selected from 431 submissions. The 4 volumes are organized in topical sections on deep and reinforcement learning; big data analysis; neural data analysis; robotics and control; bio-inspired/energy efficient information processing; whole brain architecture; neurodynamics; bioinformatics; biomedical engineering; data mining and cybersecurity workshop; machine learning; neuromorphic hardware; sensory perception; pattern recognition; social networks; brain-machine interface; computer vision; time series analysis; data-driven approach for extracting latent features; topological and graph based clustering methods; computational intelligence; data mining; deep neural networks; computational and cognitive neurosciences; theory and algorithms.

Database and Expert Systems Applications

Author : Christine Strauss
Publisher : Springer Nature
ISBN 13 : 3031398211
Total Pages : 497 pages
Book Rating : 4.0/5 (313 download)

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Book Synopsis Database and Expert Systems Applications by : Christine Strauss

Download or read book Database and Expert Systems Applications written by Christine Strauss and published by Springer Nature. This book was released on 2023-08-15 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set, LNCS 14146 and 14147 constitutes the thoroughly refereed proceedings of the 34th International Conference on Database and Expert Systems Applications, DEXA 2023, held in Penang, Malaysia, in August 2023. The 49 full papers presented together with 35 short papers were carefully reviewed and selected from a total of 155 submissions. The papers are organized in topical sections as follows: Part I: Data modeling; database design; query optimization; knowledge representation; Part II: Rule-based systems; natural language processing; deep learning; neural networks.

Neural Information Processing

Author : Derong Liu
Publisher : Springer
ISBN 13 : 3319700871
Total Pages : 951 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis Neural Information Processing by : Derong Liu

Download or read book Neural Information Processing written by Derong Liu and published by Springer. This book was released on 2017-11-07 with total page 951 pages. Available in PDF, EPUB and Kindle. Book excerpt: The six volume set LNCS 10634, LNCS 10635, LNCS 10636, LNCS 10637, LNCS 10638, and LNCS 10639 constitues the proceedings of the 24rd International Conference on Neural Information Processing, ICONIP 2017, held in Guangzhou, China, in November 2017. The 563 full papers presented were carefully reviewed and selected from 856 submissions. The 6 volumes are organized in topical sections on Machine Learning, Reinforcement Learning, Big Data Analysis, Deep Learning, Brain-Computer Interface, Computational Finance, Computer Vision, Neurodynamics, Sensory Perception and Decision Making, Computational Intelligence, Neural Data Analysis, Biomedical Engineering, Emotion and Bayesian Networks, Data Mining, Time-Series Analysis, Social Networks, Bioinformatics, Information Security and Social Cognition, Robotics and Control, Pattern Recognition, Neuromorphic Hardware and Speech Processing.

Neural Information Processing

Author : Mohammad Tanveer
Publisher : Springer Nature
ISBN 13 : 9819916399
Total Pages : 741 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Neural Information Processing by : Mohammad Tanveer

Download or read book Neural Information Processing written by Mohammad Tanveer and published by Springer Nature. This book was released on 2023-04-14 with total page 741 pages. Available in PDF, EPUB and Kindle. Book excerpt: The four-volume set CCIS 1791, 1792, 1793 and 1794 constitutes the refereed proceedings of the 29th International Conference on Neural Information Processing, ICONIP 2022, held as a virtual event, November 22–26, 2022. The 213 papers presented in the proceedings set were carefully reviewed and selected from 810 submissions. They were organized in topical sections as follows: Theory and Algorithms; Cognitive Neurosciences; Human Centered Computing; and Applications. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements.

Artificial Neural Networks and Machine Learning – ICANN 2020

Author : Igor Farkaš
Publisher : Springer Nature
ISBN 13 : 3030616169
Total Pages : 891 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Artificial Neural Networks and Machine Learning – ICANN 2020 by : Igor Farkaš

Download or read book Artificial Neural Networks and Machine Learning – ICANN 2020 written by Igor Farkaš and published by Springer Nature. This book was released on 2020-10-17 with total page 891 pages. Available in PDF, EPUB and Kindle. Book excerpt: The proceedings set LNCS 12396 and 12397 constitute the proceedings of the 29th International Conference on Artificial Neural Networks, ICANN 2020, held in Bratislava, Slovakia, in September 2020.* The total of 139 full papers presented in these proceedings was carefully reviewed and selected from 249 submissions. They were organized in 2 volumes focusing on topics such as adversarial machine learning, bioinformatics and biosignal analysis, cognitive models, neural network theory and information theoretic learning, and robotics and neural models of perception and action. *The conference was postponed to 2021 due to the COVID-19 pandemic.

Advances in Knowledge Discovery and Data Mining

Author : Tru Cao
Publisher : Springer
ISBN 13 : 331918038X
Total Pages : 785 pages
Book Rating : 4.3/5 (191 download)

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Book Synopsis Advances in Knowledge Discovery and Data Mining by : Tru Cao

Download or read book Advances in Knowledge Discovery and Data Mining written by Tru Cao and published by Springer. This book was released on 2015-04-16 with total page 785 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set, LNAI 9077 + 9078, constitutes the refereed proceedings of the 19th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2015, held in Ho Chi Minh City, Vietnam, in May 2015. The proceedings contain 117 paper carefully reviewed and selected from 405 submissions. They have been organized in topical sections named: social networks and social media; classification; machine learning; applications; novel methods and algorithms; opinion mining and sentiment analysis; clustering; outlier and anomaly detection; mining uncertain and imprecise data; mining temporal and spatial data; feature extraction and selection; mining heterogeneous, high-dimensional and sequential data; entity resolution and topic-modeling; itemset and high-performance data mining; and recommendations.

Cyber Intelligence and Information Retrieval

Author : João Manuel R. S. Tavares
Publisher : Springer Nature
ISBN 13 : 9811642842
Total Pages : 630 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Cyber Intelligence and Information Retrieval by : João Manuel R. S. Tavares

Download or read book Cyber Intelligence and Information Retrieval written by João Manuel R. S. Tavares and published by Springer Nature. This book was released on 2021-09-28 with total page 630 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers a collection of high-quality peer-reviewed research papers presented at International Conference on Cyber Intelligence and Information Retrieval (CIIR 2021), held at Institute of Engineering & Management, Kolkata, India during 20–21 May 2021. The book covers research papers in the field of privacy and security in the cloud, data loss prevention and recovery, high-performance networks, network security and cryptography, image and signal processing, artificial immune systems, information and network security, data science techniques and applications, data warehousing and data mining, data mining in dynamic environment, higher-order neural computing, rough set and fuzzy set theory, and nature-inspired computing techniques.

Machine Learning and Knowledge Discovery in Databases

Author : Toon Calders
Publisher : Springer
ISBN 13 : 3662448513
Total Pages : 746 pages
Book Rating : 4.6/5 (624 download)

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Book Synopsis Machine Learning and Knowledge Discovery in Databases by : Toon Calders

Download or read book Machine Learning and Knowledge Discovery in Databases written by Toon Calders and published by Springer. This book was released on 2014-09-01 with total page 746 pages. Available in PDF, EPUB and Kindle. Book excerpt: This three-volume set LNAI 8724, 8725 and 8726 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2014, held in Nancy, France, in September 2014. The 115 revised research papers presented together with 13 demo track papers, 10 nectar track papers, 8 PhD track papers, and 9 invited talks were carefully reviewed and selected from 550 submissions. The papers cover the latest high-quality interdisciplinary research results in all areas related to machine learning and knowledge discovery in databases.

On the Move to Meaningful Internet Systems: OTM 2019 Conferences

Author : Hervé Panetto
Publisher : Springer Nature
ISBN 13 : 3030332462
Total Pages : 781 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis On the Move to Meaningful Internet Systems: OTM 2019 Conferences by : Hervé Panetto

Download or read book On the Move to Meaningful Internet Systems: OTM 2019 Conferences written by Hervé Panetto and published by Springer Nature. This book was released on 2019-10-10 with total page 781 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume LNCS 11877 constitutes the refereed proceedings of the Confederated International Conferences: Cooperative Information Systems, CoopIS 2019, Ontologies, Databases, and Applications of Semantics, ODBASE 2019, and Cloud and Trusted Computing, C&TC, held as part of OTM 2019 in October 2019 in Rhodes, Greece. The 38 full papers presented together with 8 short papers were carefully reviewed and selected from 156 submissions. The OTM program every year covers data and Web semantics, distributed objects, Web services, databases, informationsystems, enterprise workflow and collaboration, ubiquity, interoperability, mobility, grid and high-performance computing.

Machine Learning and Knowledge Discovery in Databases

Author : Annalisa Appice
Publisher : Springer
ISBN 13 : 3319235281
Total Pages : 760 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Machine Learning and Knowledge Discovery in Databases by : Annalisa Appice

Download or read book Machine Learning and Knowledge Discovery in Databases written by Annalisa Appice and published by Springer. This book was released on 2015-08-28 with total page 760 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Multilabel Classification

Author : Francisco Herrera
Publisher : Springer
ISBN 13 : 331941111X
Total Pages : 200 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Multilabel Classification by : Francisco Herrera

Download or read book Multilabel Classification written by Francisco Herrera and published by Springer. This book was released on 2016-08-09 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a comprehensive review of multilabel techniques widely used to classify and label texts, pictures, videos and music in the Internet. A deep review of the specialized literature on the field includes the available software needed to work with this kind of data. It provides the user with the software tools needed to deal with multilabel data, as well as step by step instruction on how to use them. The main topics covered are: • The special characteristics of multi-labeled data and the metrics available to measure them.• The importance of taking advantage of label correlations to improve the results.• The different approaches followed to face multi-label classification.• The preprocessing techniques applicable to multi-label datasets.• The available software tools to work with multi-label data. This book is beneficial for professionals and researchers in a variety of fields because of the wide range of potential applications for multilabel classification. Besides its multiple applications to classify different types of online information, it is also useful in many other areas, such as genomics and biology. No previous knowledge about the subject is required. The book introduces all the needed concepts to understand multilabel data characterization, treatment and evaluation.

Matrix decomposition methods for data mining

Author : Pauli Miettinen
Publisher :
ISBN 13 : 9789521054976
Total Pages : 170 pages
Book Rating : 4.0/5 (549 download)

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Book Synopsis Matrix decomposition methods for data mining by : Pauli Miettinen

Download or read book Matrix decomposition methods for data mining written by Pauli Miettinen and published by . This book was released on 2009 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Optimization for Machine Learning

Author : Suvrit Sra
Publisher : MIT Press
ISBN 13 : 026201646X
Total Pages : 509 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis Optimization for Machine Learning by : Suvrit Sra

Download or read book Optimization for Machine Learning written by Suvrit Sra and published by MIT Press. This book was released on 2012 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt: An up-to-date account of the interplay between optimization and machine learning, accessible to students and researchers in both communities. The interplay between optimization and machine learning is one of the most important developments in modern computational science. Optimization formulations and methods are proving to be vital in designing algorithms to extract essential knowledge from huge volumes of data. Machine learning, however, is not simply a consumer of optimization technology but a rapidly evolving field that is itself generating new optimization ideas. This book captures the state of the art of the interaction between optimization and machine learning in a way that is accessible to researchers in both fields. Optimization approaches have enjoyed prominence in machine learning because of their wide applicability and attractive theoretical properties. The increasing complexity, size, and variety of today's machine learning models call for the reassessment of existing assumptions. This book starts the process of reassessment. It describes the resurgence in novel contexts of established frameworks such as first-order methods, stochastic approximations, convex relaxations, interior-point methods, and proximal methods. It also devotes attention to newer themes such as regularized optimization, robust optimization, gradient and subgradient methods, splitting techniques, and second-order methods. Many of these techniques draw inspiration from other fields, including operations research, theoretical computer science, and subfields of optimization. The book will enrich the ongoing cross-fertilization between the machine learning community and these other fields, and within the broader optimization community.

Learning from Imbalanced Data Sets

Author : Alberto Fernández
Publisher : Springer
ISBN 13 : 3319980742
Total Pages : 385 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Learning from Imbalanced Data Sets by : Alberto Fernández

Download or read book Learning from Imbalanced Data Sets written by Alberto Fernández and published by Springer. This book was released on 2018-10-22 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a general and comprehensible overview of imbalanced learning. It contains a formal description of a problem, and focuses on its main features, and the most relevant proposed solutions. Additionally, it considers the different scenarios in Data Science for which the imbalanced classification can create a real challenge. This book stresses the gap with standard classification tasks by reviewing the case studies and ad-hoc performance metrics that are applied in this area. It also covers the different approaches that have been traditionally applied to address the binary skewed class distribution. Specifically, it reviews cost-sensitive learning, data-level preprocessing methods and algorithm-level solutions, taking also into account those ensemble-learning solutions that embed any of the former alternatives. Furthermore, it focuses on the extension of the problem for multi-class problems, where the former classical methods are no longer to be applied in a straightforward way. This book also focuses on the data intrinsic characteristics that are the main causes which, added to the uneven class distribution, truly hinders the performance of classification algorithms in this scenario. Then, some notes on data reduction are provided in order to understand the advantages related to the use of this type of approaches. Finally this book introduces some novel areas of study that are gathering a deeper attention on the imbalanced data issue. Specifically, it considers the classification of data streams, non-classical classification problems, and the scalability related to Big Data. Examples of software libraries and modules to address imbalanced classification are provided. This book is highly suitable for technical professionals, senior undergraduate and graduate students in the areas of data science, computer science and engineering. It will also be useful for scientists and researchers to gain insight on the current developments in this area of study, as well as future research directions.