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Author: Azad Naik Publisher: Springer ISBN: 303001620X Category : Computers Languages : en Pages : 104
Book Description
This SpringerBrief covers the technical material related to large scale hierarchical classification (LSHC). HC is an important machine learning problem that has been researched and explored extensively in the past few years. In this book, the authors provide a comprehensive overview of various state-of-the-art existing methods and algorithms that were developed to solve the HC problem in large scale domains. Several challenges faced by LSHC is discussed in detail such as: 1. High imbalance between classes at different levels of the hierarchy 2. Incorporating relationships during model learning leads to optimization issues 3. Feature selection 4. Scalability due to large number of examples, features and classes 5. Hierarchical inconsistencies 6. Error propagation due to multiple decisions involved in making predictions for top-down methods The brief also demonstrates how multiple hierarchies can be leveraged for improving the HC performance using different Multi-Task Learning (MTL) frameworks. The purpose of this book is two-fold: 1. Help novice researchers/beginners to get up to speed by providing a comprehensive overview of several existing techniques. 2. Provide several research directions that have not yet been explored extensively to advance the research boundaries in HC. New approaches discussed in this book include detailed information corresponding to the hierarchical inconsistencies, multi-task learning and feature selection for HC. Its results are highly competitive with the state-of-the-art approaches in the literature.
Author: Azad Naik Publisher: Springer ISBN: 303001620X Category : Computers Languages : en Pages : 104
Book Description
This SpringerBrief covers the technical material related to large scale hierarchical classification (LSHC). HC is an important machine learning problem that has been researched and explored extensively in the past few years. In this book, the authors provide a comprehensive overview of various state-of-the-art existing methods and algorithms that were developed to solve the HC problem in large scale domains. Several challenges faced by LSHC is discussed in detail such as: 1. High imbalance between classes at different levels of the hierarchy 2. Incorporating relationships during model learning leads to optimization issues 3. Feature selection 4. Scalability due to large number of examples, features and classes 5. Hierarchical inconsistencies 6. Error propagation due to multiple decisions involved in making predictions for top-down methods The brief also demonstrates how multiple hierarchies can be leveraged for improving the HC performance using different Multi-Task Learning (MTL) frameworks. The purpose of this book is two-fold: 1. Help novice researchers/beginners to get up to speed by providing a comprehensive overview of several existing techniques. 2. Provide several research directions that have not yet been explored extensively to advance the research boundaries in HC. New approaches discussed in this book include detailed information corresponding to the hierarchical inconsistencies, multi-task learning and feature selection for HC. Its results are highly competitive with the state-of-the-art approaches in the literature.
Author: Azad Naik Publisher: ISBN: 9783030016210 Category : Supervised learning (Machine learning) Languages : en Pages : 93
Book Description
This SpringerBrief covers the technical material related to large scale hierarchical classification (LSHC). HC is an important machine learning problem that has been researched and explored extensively in the past few years. In this book, the authors provide a comprehensive overview of various state-of-the-art existing methods and algorithms that were developed to solve the HC problem in large scale domains. Several challenges faced by LSHC is discussed in detail such as: 1. High imbalance between classes at different levels of the hierarchy; 2. Incorporating relationships during model learning leads to optimization issues; 3. Feature selection; 4. Scalability due to large number of examples, features and classes; 5. Hierarchical inconsistencies; 6. Error propagation due to multiple decisions involved in making predictions for top-down methods. The brief also demonstrates how multiple hierarchies can be leveraged for improving the HC performance using different Multi-Task Learning (MTL) frameworks.
Author: Shuigeng Zhou Publisher: Springer Science & Business Media ISBN: 3642355277 Category : Computers Languages : en Pages : 812
Book Description
This book constitutes the refereed proceedings of the 8th International Conference on Advanced Data Mining and Applications, ADMA 2012, held in Nanjing, China, in December 2012. The 32 regular papers and 32 short papers presented in this volume were carefully reviewed and selected from 168 submissions. They are organized in topical sections named: social media mining; clustering; machine learning: algorithms and applications; classification; prediction, regression and recognition; optimization and approximation; mining time series and streaming data; Web mining and semantic analysis; data mining applications; search and retrieval; information recommendation and hiding; outlier detection; topic modeling; and data cube computing.
Author: Igor Farkaš Publisher: Springer Nature ISBN: 3030616169 Category : Computers Languages : en Pages : 891
Book Description
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.
Author: Faisal Saeed Publisher: Springer Nature ISBN: 3030987418 Category : Computers Languages : en Pages : 793
Book Description
This book presents emerging trends in intelligent computing and informatics. This book presents the papers included in the proceedings of the 6th International Conference of Reliable Information and Communication Technology 2021 (IRICT 2021) that was held virtually, on Dec. 22-23, 2021. The main theme of the book is “Advances on Intelligent Informatics and Computing”. A total of 87 papers were submitted to the conference, but only 66 papers were accepted and published in this book. The book presents several hot research topics which include health informatics, artificial intelligence, soft computing, data science, big data analytics, Internet of Things (IoT), intelligent communication systems, cybersecurity, and information systems.
Author: Evangelos Kanoulas Publisher: Springer ISBN: 3319113828 Category : Computers Languages : en Pages : 340
Book Description
This book constitutes the refereed proceedings of the 5th International Conference of the CLEF Initiative, CLEF 2014, held in Sheffield, UK, in September 2014. The 11 full papers and 5 short papers presented were carefully reviewed and selected from 30 submissions. They cover a broad range of issues in the fields of multilingual and multimodal information access evaluation, also included are a set of labs and workshops designed to test different aspects of mono and cross-language information retrieval systems
Author: Jennifer S. Raj Publisher: Springer Nature ISBN: 9819917263 Category : Technology & Engineering Languages : en Pages : 866
Book Description
This book features research papers presented at the 6th International Conference on Intelligent Sustainable Systems (ICISS 2023), held at SCAD College of Engineering and Technology, Tirunelveli, Tamil Nadu, India, during February 2–3, 2023. The book reports research results on the development and implementation of novel systems, technologies, and applications that focus on the advancement of sustainable living. The chapters included in this book discuss a spectrum of related research issues such as applications of intelligent computing practices that can have ecological and societal impacts. Moreover, this book emphasizes on the state-of-the-art networked and intelligent technologies that are influencing a promising development in the direction of a long-term sustainable future. The book is beneficial for readers from both academia and industry.
Author: Hendrik Blockeel Publisher: Springer ISBN: 9781461411468 Category : Computers Languages : en Pages : 240
Book Description
This book introduces a novel paradigm for machine learning and data mining called predictive clustering, which covers a broad variety of learning tasks and offers a fresh perspective on existing techniques. The book presents an informal introduction to predictive clustering, describing learning tasks and settings, and then continues with a formal description of the paradigm, explaining algorithms for learning predictive clustering trees and predictive clustering rules, as well as presenting the applicability of these learning techniques to a broad range of tasks. Variants of decision tree learning algorithms are also introduced. Finally, the book offers several significant applications in ecology and bio-informatics. The book is written in a straightforward and easy-to-understand manner, aimed at varied readership, ranging from researchers with an interest in machine learning techniques to practitioners of data mining technology in the areas of ecology and bioinformatics.
Author: Zhouchen Lin Publisher: Springer Nature ISBN: 3030317269 Category : Computers Languages : en Pages : 562
Book Description
The three-volume set LNCS 11857, 11858, and 11859 constitutes the refereed proceedings of the Second Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2019, held in Xi’an, China, in November 2019. The 165 revised full papers presented were carefully reviewed and selected from 412 submissions. The papers have been organized in the following topical sections: Part I: Object Detection, Tracking and Recognition, Part II: Image/Video Processing and Analysis, Part III: Data Analysis and Optimization.
Author: Annalisa Appice Publisher: Springer ISBN: 3319235281 Category : Computers Languages : en Pages : 760
Book Description
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.
Author: Azad Naik
Author: Azad Naik
Author: Azad Naik
Author: Shuigeng Zhou
Author: Igor Farkaš
Author: Faisal Saeed
Author: Evangelos Kanoulas
Author: Jennifer S. Raj
Author: Hendrik Blockeel
Author: Zhouchen Lin
Author: Annalisa Appice