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

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  • 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 Neural Information Processing Systems 19

Advances in Neural Information Processing Systems 19
  • Author : Bernhard Schölkopf,John Platt,Thomas Hofmann
  • Publisher : MIT Press
  • Release : 09 December 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.

Harmonic Modeling of Voltage Source Converters using Basic Numerical Methods

Harmonic Modeling of Voltage Source Converters using Basic Numerical Methods
  • Author : Ryan Kuo-Lung Lian,Ramadhani Kurniawan Subroto,Victor Andrean,Bing Hao Lin
  • Publisher : John Wiley & Sons
  • Release : 01 November 2021
GET THIS BOOKHarmonic Modeling of Voltage Source Converters using Basic Numerical Methods

Harmonic Modeling of Voltage Source Converters using Basic Numerical Methods One of the first books to bridge the gap between frequency domain and time-domain methods of steady-state modeling of power electronic converters Harmonic Modeling of Voltage Source Converters using Basic Numerical Methods presents detailed coverage of steady-state modeling of power electronic devices (PEDs). This authoritative resource describes both large-signal and small-signal modeling of power converters and how some of the simple and commonly used numerical methods can be applied for

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.

Advances in Knowledge Discovery and Data Mining

Advances in Knowledge Discovery and Data Mining
  • Author : Kamal Karlapalem,Hong Cheng,Naren Ramakrishnan,R. K. Agrawal,P. Krishna Reddy,Jaideep Srivastava,Tanmoy Chakraborty
  • Publisher : Springer Nature
  • Release : 08 May 2021
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The 3-volume set LNAI 12712-12714 constitutes the proceedings of the 25th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2021, which was held during May 11-14, 2021. The 157 papers included in the proceedings were carefully reviewed and selected from a total of 628 submissions. They were organized in topical sections as follows: Part I: Applications of knowledge discovery and data mining of specialized data; Part II: Classical data mining; data mining theory and principles; recommender systems; and text analytics; Part

Runtime Verification

Runtime Verification
  • Author : Lu Feng,Dana Fisman
  • Publisher : Springer Nature
  • Release : 05 October 2021
GET THIS BOOKRuntime Verification

This book constitutes the refereed proceedings of the 21st International Conference on Runtime Verification, RV 2021, held virtually during October 11-14, 2021. The 11 regular papers and 7 short/tool/benchmark papers presented in this book were carefully reviewed and selected from 40 submissions. Also included is one tutorial paper. The RV conference is concerned with all aspects of monitoring and analysis of hardware, software and more general system executions.

Advances in Machine Learning

Advances in Machine Learning
  • Author : Zhi-Hua Zhou,Takashi Washio
  • Publisher : Springer
  • Release : 03 November 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

Deep Learning for the Earth Sciences

Deep Learning for the Earth Sciences
  • Author : Gustau Camps-Valls,Devis Tuia,Xiao Xiang Zhu,Markus Reichstein
  • Publisher : John Wiley & Sons
  • Release : 18 August 2021
GET THIS BOOKDeep Learning for the Earth Sciences

DEEP LEARNING FOR THE EARTH SCIENCES Explore this insightful treatment of deep learning in the field of earth sciences, from four leading voices Deep learning is a fundamental technique in modern Artificial Intelligence and is being applied to disciplines across the scientific spectrum; earth science is no exception. Yet, the link between deep learning and Earth sciences has only recently entered academic curricula and thus has not yet proliferated. Deep Learning for the Earth Sciences delivers a unique perspective and

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.

AI*IA 2005: Advances in Artificial Intelligence

AI*IA 2005: Advances in Artificial Intelligence
  • Author : Associazione italiana per l'intelligenza artificiale. Congress,Associazione Italiana per l'Intelligenza Artificiale
  • Publisher : Springer Science & Business Media
  • Release : 12 September 2005
GET THIS BOOKAI*IA 2005: Advances in Artificial Intelligence

This book constitutes the refereed proceedings of the 9th Congress of the Italian Association for Artificial Intelligence, AI*IA 2005, held in Milan, Italy in September 2005. The 46 revised full papers presented together with 16 revised short papers were carefully reviewed and selected for inclusion in the book. The papers are organized in topical sections on either theoretical research with results and proposals, improvements and consolidations, or on applications as there are systems and prototypes, case studies and proposals. Within this classification some

Advances in Data Science and Information Engineering

Advances in Data Science and Information Engineering
  • Author : Robert Stahlbock,Gary M. Weiss,Mahmoud Abou-Nasr,Cheng-Ying Yang,Hamid R. Arabnia,Leonidas Deligiannidis
  • Publisher : Springer Nature
  • Release : 29 October 2021
GET THIS BOOKAdvances in Data Science and Information Engineering

The book presents the proceedings of two conferences: the 16th International Conference on Data Science (ICDATA 2020) and the 19th International Conference on Information & Knowledge Engineering (IKE 2020), which took place in Las Vegas, NV, USA, July 27-30, 2020. The conferences are part of the larger 2020 World Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE'20), which features 20 major tracks. Papers cover all aspects of Data Science, Data Mining, Machine Learning, Artificial and Computational Intelligence (ICDATA) and Information Retrieval Systems, Information & Knowledge Engineering,

Machine Learning and Knowledge Discovery in Databases

Machine Learning and Knowledge Discovery in Databases
  • Author : Frank Hutter,Tijl De Bie,Kristian Kersting,Jefrey Lijffijt,Isabel Valera
  • Publisher : Springer Nature
  • Release : 09 December 2021
GET THIS BOOKMachine Learning and Knowledge Discovery in Databases

The 5-volume proceedings, LNAI 12457 until 12461 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2020, which was held during September 14-18, 2020. The conference was planned to take place in Ghent, Belgium, but had to change to an online format due to the COVID-19 pandemic. The 232 full papers and 10 demo papers presented in this volume were carefully reviewed and selected for inclusion in the proceedings. The volumes are organized in topical sections as

Advances in Systems Science

Advances in Systems Science
  • Author : Jerzy Świątek,Jakub M. Tomczak
  • Publisher : Springer
  • Release : 04 November 2016
GET THIS BOOKAdvances in Systems Science

This book gathers the carefully reviewed proceedings of the 19th International Conference on Systems Science, presenting recent research findings in the areas of Artificial Intelligence, Machine Learning, Communication/Networking and Information Technology, Control Theory, Decision Support, Image Processing and Computer Vision, Optimization Techniques, Pattern Recognition, Robotics, Service Science, Web-based Services, Uncertain Systems and Transportation Systems. The International Conference on Systems Science was held in Wroclaw, Poland from September 7 to 9, 2016, and addressed a range of topics, including systems theory, control theory,

Advances in Knowledge Discovery and Data Mining

Advances in Knowledge Discovery and Data Mining
  • Author : Vincent S. Tseng,Tu Bao Ho,Zhi-Hua Zhou,Arbee L.P. Chen,Hung-Yu Kao
  • Publisher : Springer
  • Release : 08 May 2014
GET THIS BOOKAdvances in Knowledge Discovery and Data Mining

The two-volume set LNAI 8443 + LNAI 8444 constitutes the refereed proceedings of the 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2014, held in Tainan, Taiwan, in May 2014. The 40 full papers and the 60 short papers presented within these proceedings were carefully reviewed and selected from 371 submissions. They cover the general fields of pattern mining; social network and social media; classification; graph and network mining; applications; privacy preserving; recommendation; feature selection and reduction; machine learning; temporal and spatial data; novel algorithms; clustering;