Advances in Domain Adaptation Theory

Advances in Domain Adaptation Theory gives current, state-of-the-art results on transfer learning, with a particular focus placed on domain adaptation from a theoretical point-of-view. The book begins with a brief overview of the most popular concepts used to provide generalization guarantees, including sections on Vapnik-Chervonenkis (VC), Rademacher, PAC-Bayesian, Robustness and Stability based bounds. In addition, the book explains domain adaptation problem and describes the four major families of theoretical results that exist in the literature, including the Divergence based bounds. Next, PAC-Bayesian bounds are discussed, including the original PAC-Bayesian bounds for domain adaptation and their updated version. Additional sections present generalization guarantees based on the robustness and stability properties of the learning algorithm. Gives an overview of current results on transfer learning Focuses on the adaptation of the field from a theoretical point-of-view Describes four major families of theoretical results in the literature Summarizes existing results on adaptation in the field Provides tips for future research

Produk Detail:

  • Author : Ievgen Redko
  • Publisher : Elsevier
  • Pages : 208 pages
  • ISBN : 0081023472
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKAdvances in Domain Adaptation Theory

Advances in Domain Adaptation Theory

Advances in Domain Adaptation Theory
  • Author : Ievgen Redko,Emilie Morvant,Amaury Habrard,Marc Sebban,Younès Bennani
  • Publisher : Elsevier
  • Release : 23 August 2019
GET THIS BOOKAdvances in Domain Adaptation Theory

Advances in Domain Adaptation Theory gives current, state-of-the-art results on transfer learning, with a particular focus placed on domain adaptation from a theoretical point-of-view. The book begins with a brief overview of the most popular concepts used to provide generalization guarantees, including sections on Vapnik-Chervonenkis (VC), Rademacher, PAC-Bayesian, Robustness and Stability based bounds. In addition, the book explains domain adaptation problem and describes the four major families of theoretical results that exist in the literature, including the Divergence based bounds.

Advances in Intelligent Data Analysis XVIII

Advances in Intelligent Data Analysis XVIII
  • Author : Michael R. Berthold,Ad Feelders,Georg Krempl
  • Publisher : Springer Nature
  • Release : 22 April 2020
GET THIS BOOKAdvances in Intelligent Data Analysis XVIII

This open access book constitutes the proceedings of the 18th International Conference on Intelligent Data Analysis, IDA 2020, held in Konstanz, Germany, in April 2020. The 45 full papers presented in this volume were carefully reviewed and selected from 114 submissions. Advancing Intelligent Data Analysis requires novel, potentially game-changing ideas. IDA’s mission is to promote ideas over performance: a solid motivation can be as convincing as exhaustive empirical evaluation.

Dataset Shift in Machine Learning

Dataset Shift in Machine Learning
  • Author : Joaquin Quiñonero-Candela,Masashi Sugiyama,Neil D. Lawrence,Anton Schwaighofer
  • Publisher : Neural Information Processing
  • Release : 28 January 2021
GET THIS BOOKDataset Shift in Machine Learning

An overview of recent efforts in the machine learning community to deal with dataset and covariate shift, which occurs when test and training inputs and outputs have different distributions. Dataset shift is a common problem in predictive modeling that occurs when the joint distribution of inputs and outputs differs between training and test stages. Covariate shift, a particular case of dataset shift, occurs when only the input distribution changes. Dataset shift is present in most practical applications, for reasons ranging

Advances in Data Mining. Applications and Theoretical Aspects

Advances in Data Mining. Applications and Theoretical Aspects
  • Author : Petra Perner
  • Publisher : Springer
  • Release : 04 July 2018
GET THIS BOOKAdvances in Data Mining. Applications and Theoretical Aspects

This volume constitutes the proceedings of the 18th Industrial Conference on Adances in Data Mining, ICDM 2018, held in New York, NY, USA, in July 2018. The 24 regular papers presented in this book were carefully reviewed and selected from 146 submissions. The topics range from theoretical aspects of data mining to applications of data mining, such as in multimedia data, in marketing, in medicine and agriculture, and in process control, industry, and society.

Domain Adaptation in Computer Vision Applications

Domain Adaptation in Computer Vision Applications
  • Author : Gabriela Csurka
  • Publisher : Unknown Publisher
  • Release : 28 June 2018
GET THIS BOOKDomain Adaptation in Computer Vision Applications

This comprehensive text/reference presents a broad review of diverse domain adaptation (DA) methods for machine learning, with a focus on solutions for visual applications. The book collects together solutions and perspectives proposed by an international selection of pre-eminent experts in the field, addressing not only classical image categorization, but also other computer vision tasks such as detection, segmentation and visual attributes. Topics and features: Surveys the complete field of visual DA, including shallow methods designed for homogeneous and heterogeneous

Knowledge Discovery in Databases: PKDD 2007

Knowledge Discovery in Databases: PKDD 2007
  • Author : Joost N. Kok,Jacek Koronacki,Ramon Lopez de Mantaras,Stan Matwin,Dunja Mladenic
  • Publisher : Springer
  • Release : 30 August 2007
GET THIS BOOKKnowledge Discovery in Databases: PKDD 2007

This book constitutes the refereed proceedings of the 11th European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 2007, held in Warsaw, Poland, co-located with ECML 2007, the 18th European Conference on Machine Learning. The 28 revised full papers and 35 revised short papers present original results on leading-edge subjects of knowledge discovery from conventional and complex data and address all current issues in the area.

Advances in Neural Information Processing Systems 19

Advances in Neural Information Processing Systems 19
  • Author : Bernhard Schölkopf,John Platt,Thomas Hofmann
  • Publisher : MIT Press
  • Release : 28 January 2021
GET THIS BOOKAdvances in Neural Information Processing Systems 19

The annual conference on NIPS is the flagship conference on neural computation. It draws top academic researchers from around the world & is considered to be a showcase conference for new developments in network algorithms & architectures. This volume contains all of the papers presented at NIPS 2006.

Transfer Learning

Transfer Learning
  • Author : Qiang Yang,Yu Zhang,Wenyuan Dai,Sinno Jialin Pan
  • Publisher : Cambridge University Press
  • Release : 31 January 2020
GET THIS BOOKTransfer Learning

This in-depth tutorial for students, researchers, and developers covers foundations, plus applications ranging from search to multimedia.

Recent Advances in Big Data and Deep Learning

Recent Advances in Big Data and Deep Learning
  • Author : Luca Oneto,Nicolò Navarin,Alessandro Sperduti,Davide Anguita
  • Publisher : Springer
  • Release : 02 April 2019
GET THIS BOOKRecent Advances in Big Data and Deep Learning

This book presents the original articles that have been accepted in the 2019 INNS Big Data and Deep Learning (INNS BDDL) international conference, a major event for researchers in the field of artificial neural networks, big data and related topics, organized by the International Neural Network Society and hosted by the University of Genoa. In 2019 INNS BDDL has been held in Sestri Levante (Italy) from April 16 to April 18. More than 80 researchers from 20 countries participated in the INNS BDDL in April 2019. In

Adaptation in Natural and Artificial Systems

Adaptation in Natural and Artificial Systems
  • Author : John Henry Holland,Professor of Psychology and of Electrical Engineering and Computer Science John H Holland,Senior Lecturer in Human Resource Management Holland
  • Publisher : MIT Press
  • Release : 28 January 1992
GET THIS BOOKAdaptation in Natural and Artificial Systems

List of figures. Preface to the 1992 edition. Preface. The general setting. A formal framework. lustrations. Schemata. The optimal allocation of trials. Reproductive plans and genetic operators. The robustness of genetic plans. Adaptation of codings and representations. An overview. Interim and prospectus. Glossary of important symbols.

Computer Vision – ECCV 2012

Computer Vision – ECCV 2012
  • Author : Andrew Fitzgibbon,Svetlana Lazebnik,Pietro Perona,Yoichi Sato,Cordelia Schmid
  • Publisher : Springer
  • Release : 26 September 2012
GET THIS BOOKComputer Vision – ECCV 2012

The seven-volume set comprising LNCS volumes 7572-7578 constitutes the refereed proceedings of the 12th European Conference on Computer Vision, ECCV 2012, held in Florence, Italy, in October 2012. The 408 revised papers presented were carefully reviewed and selected from 1437 submissions. The papers are organized in topical sections on geometry, 2D and 3D shapes, 3D reconstruction, visual recognition and classification, visual features and image matching, visual monitoring: action and activities, models, optimisation, learning, visual tracking and image registration, photometry: lighting and colour, and image

Person Re-Identification

Person Re-Identification
  • Author : Shaogang Gong,Marco Cristani,Shuicheng Yan,Chen Change Loy
  • Publisher : Springer Science & Business Media
  • Release : 03 January 2014
GET THIS BOOKPerson Re-Identification

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

Advances in Machine Learning

Advances in Machine Learning
  • Author : Zhi-Hua Zhou,Takashi Washio
  • Publisher : Springer Science & Business Media
  • Release : 06 October 2009
GET THIS BOOKAdvances in Machine Learning

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