Learning With Kernels
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Learning With Kernels
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Author : Bernhard Scholkopf
language : en
Publisher: MIT Press
Release Date : 2018-06-05
Learning With Kernels written by Bernhard Scholkopf and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-05 with Computers categories.
A comprehensive introduction to Support Vector Machines and related kernel methods. In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs—-kernels—for a number of learning tasks. Kernel machines provide a modular framework that can be adapted to different tasks and domains by the choice of the kernel function and the base algorithm. They are replacing neural networks in a variety of fields, including engineering, information retrieval, and bioinformatics. Learning with Kernels provides an introduction to SVMs and related kernel methods. Although the book begins with the basics, it also includes the latest research. It provides all of the concepts necessary to enable a reader equipped with some basic mathematical knowledge to enter the world of machine learning using theoretically well-founded yet easy-to-use kernel algorithms and to understand and apply the powerful algorithms that have been developed over the last few years.
Learning With Kernels Support Vector Machines Regularization Optimizat
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Author : SCHOLKOPF SMOLA.
language : en
Publisher:
Release Date :
Learning With Kernels Support Vector Machines Regularization Optimizat written by SCHOLKOPF SMOLA. and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Learning With Kernels
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Author : Alexander Johannes Smola
language : en
Publisher:
Release Date : 1998
Learning With Kernels written by Alexander Johannes Smola and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with categories.
Advances In Kernel Methods
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Author : Bernhard Schölkopf
language : en
Publisher: MIT Press
Release Date : 1999
Advances In Kernel Methods written by Bernhard Schölkopf and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Computers categories.
A young girl hears the story of her great-great-great-great- grandfather and his brother who came to the United States to make a better life for themselves helping to build the transcontinental railroad.
Algorithmic Learning Theory
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Author : Marcus Hutter
language : en
Publisher: Springer
Release Date : 2010-09-02
Algorithmic Learning Theory written by Marcus Hutter and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-09-02 with Computers categories.
This volume contains the papers presented at the 21st International Conf- ence on Algorithmic Learning Theory (ALT 2010), which was held in Canberra, Australia, October 6–8, 2010. The conference was co-located with the 13th - ternational Conference on Discovery Science (DS 2010) and with the Machine Learning Summer School, which was held just before ALT 2010. The tech- cal program of ALT 2010, contained 26 papers selected from 44 submissions and ?ve invited talks. The invited talks were presented in joint sessions of both conferences. ALT 2010 was dedicated to the theoretical foundations of machine learning and took place on the campus of the Australian National University, Canberra, Australia. ALT provides a forum for high-quality talks with a strong theore- cal background and scienti?c interchange in areas such as inductive inference, universal prediction, teaching models, grammatical inference, formal languages, inductive logic programming, query learning, complexity of learning, on-line learning and relative loss bounds, semi-supervised and unsupervised learning, clustering,activelearning,statisticallearning,supportvectormachines,Vapnik- Chervonenkisdimension,probablyapproximatelycorrectlearning,Bayesianand causal networks, boosting and bagging, information-based methods, minimum descriptionlength,Kolmogorovcomplexity,kernels,graphlearning,decisiontree methods, Markov decision processes, reinforcement learning, and real-world - plications of algorithmic learning theory. DS 2010 was the 13th International Conference on Discovery Science and focused on the development and analysis of methods for intelligent data an- ysis, knowledge discovery and machine learning, as well as their application to scienti?c knowledge discovery. As is the tradition, it was co-located and held in parallel with Algorithmic Learning Theory.
Machine Learning And Knowledge Discovery In Databases
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Author : Walter Daelemans
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-09-04
Machine Learning And Knowledge Discovery In Databases written by Walter Daelemans and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-09-04 with Computers categories.
This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2008, held in Antwerp, Belgium, in September 2008. The 100 papers presented in two volumes, together with 5 invited talks, were carefully reviewed and selected from 521 submissions. In addition to the regular papers the volume contains 14 abstracts of papers appearing in full version in the Machine Learning Journal and the Knowledge Discovery and Databases Journal of Springer. The conference intends to provide an international forum for the discussion of the latest high quality research results in all areas related to machine learning and knowledge discovery in databases. The topics addressed are application of machine learning and data mining methods to real-world problems, particularly exploratory research that describes novel learning and mining tasks and applications requiring non-standard techniques.
Artificial Neural Networks And Machine Learning Icann 2024
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Author : Michael Wand
language : en
Publisher: Springer Nature
Release Date : 2024-09-16
Artificial Neural Networks And Machine Learning Icann 2024 written by Michael Wand and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-16 with Computers categories.
The ten-volume set LNCS 15016-15025 constitutes the refereed proceedings of the 33rd International Conference on Artificial Neural Networks and Machine Learning, ICANN 2024, held in Lugano, Switzerland, during September 17–20, 2024. The 294 full papers and 16 short papers included in these proceedings were carefully reviewed and selected from 764 submissions. The papers cover the following topics: Part I - theory of neural networks and machine learning; novel methods in machine learning; novel neural architectures; neural architecture search; self-organization; neural processes; novel architectures for computer vision; and fairness in machine learning. Part II - computer vision: classification; computer vision: object detection; computer vision: security and adversarial attacks; computer vision: image enhancement; and computer vision: 3D methods. Part III - computer vision: anomaly detection; computer vision: segmentation; computer vision: pose estimation and tracking; computer vision: video processing; computer vision: generative methods; and topics in computer vision. Part IV - brain-inspired computing; cognitive and computational neuroscience; explainable artificial intelligence; robotics; and reinforcement learning. Part V - graph neural networks; and large language models. Part VI - multimodality; federated learning; and time series processing. Part VII - speech processing; natural language processing; and language modeling. Part VIII - biosignal processing in medicine and physiology; and medical image processing. Part IX - human-computer interfaces; recommender systems; environment and climate; city planning; machine learning in engineering and industry; applications in finance; artificial intelligence in education; social network analysis; artificial intelligence and music; and software security. Part X - workshop: AI in drug discovery; workshop: reservoir computing; special session: accuracy, stability, and robustness in deep neural networks; special session: neurorobotics; and special session: spiking neural networks.
Semi Supervised Learning With Kernels
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Author : Zalán Péter Bodó
language : en
Publisher:
Release Date : 2009
Semi Supervised Learning With Kernels written by Zalán Péter Bodó and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with categories.
Learning With Multiple Kernels
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Author : Gert René Georges Lanckriet
language : en
Publisher:
Release Date : 2005
Learning With Multiple Kernels written by Gert René Georges Lanckriet and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with categories.
Advances In Machine Learning
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Author : Zhi-Hua Zhou
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-10-06
Advances In Machine Learning written by Zhi-Hua Zhou and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-10-06 with Computers categories.
The First Asian Conference on Machine Learning (ACML 2009) was held at Nanjing, China during November 2–4, 2009.This was the ?rst edition of a series of annual conferences which aim to provide a leading international forum for researchers in machine learning and related ?elds to share their new ideas and research ?ndings. This year we received 113 submissions from 18 countries and regions in Asia, Australasia, Europe and North America. The submissions went through a r- orous double-blind reviewing process. Most submissions received four reviews, a few submissions received ?ve reviews, while only several submissions received three reviews. Each submission was handled by an Area Chair who coordinated discussions among reviewers and made recommendation on the submission. The Program Committee Chairs examined the reviews and meta-reviews to further guarantee the reliability and integrity of the reviewing process. Twenty-nine - pers were selected after this process. To ensure that important revisions required by reviewers were incorporated into the ?nal accepted papers, and to allow submissions which would have - tential after a careful revision, this year we launched a “revision double-check” process. In short, the above-mentioned 29 papers were conditionally accepted, and the authors were requested to incorporate the “important-and-must”re- sionssummarizedbyareachairsbasedonreviewers’comments.Therevised?nal version and the revision list of each conditionally accepted paper was examined by the Area Chair and Program Committee Chairs. Papers that failed to pass the examination were ?nally rejected.