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Advances in Domain Adaptation Theory

Advances in Domain Adaptation Theory
  • Author : Ievgen Redko,Emilie Morvant,Amaury Habrard,Marc Sebban,Younès Bennani
  • Publisher :Unknown
  • Release Date :2019-08-23
  • Total pages :208
  • ISBN : 9780081023471
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Summary : 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

Advances in Neural Information Processing Systems 19

Advances in Neural Information Processing Systems 19
  • Author : Bernhard Schölkopf,John Platt,Thomas Hofmann
  • Publisher :Unknown
  • Release Date :2007
  • Total pages :1643
  • ISBN : 9780262195683
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Summary : 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.

Advances in Machine Learning

Advances in Machine Learning
  • Author : Zhi-Hua Zhou,Takashi Washio
  • Publisher :Unknown
  • Release Date :2009-11-03
  • Total pages :413
  • ISBN : 9783642052248
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Summary : 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.

Advances in Intelligent Data Analysis XVIII

Advances in Intelligent Data Analysis XVIII
  • Author : Michael R. Berthold,Ad Feelders,Georg Krempl
  • Publisher :Unknown
  • Release Date :2020-04-22
  • Total pages :588
  • ISBN : 9783030445843
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Summary : 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 :Unknown
  • Release Date :2009
  • Total pages :229
  • ISBN : UOM:39015080846309
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Summary : 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 from the bias introduced by experimental design to the irreproducibility of the testing conditions at training time. (An example is -email spam filtering, which may fail to recognize spam that differs in form from the spam the automatic filter has been built on.) Despite this, and despite the attention given to the apparently similar problems of semi-supervised learning and active learning, dataset shift has received relatively little attention in the machine learning community until recently. This volume offers an overview of current efforts to deal with dataset and covariate shift. The chapters offer a mathematical and philosophical introduction to the problem, place dataset shift in relationship to transfer learning, transduction, local learning, active learning, and semi-supervised learning, provide theoretical views of dataset and covariate shift (including decision theoretic and Bayesian perspectives), and present algorithms for covariate shift. Contributors Shai Ben-David, Steffen Bickel, Karsten Borgwardt, Michael Brückner, David Corfield, Amir Globerson, Arthur Gretton, Lars Kai Hansen, Matthias Hein, Jiayuan Huang, Choon Hui Teo, Takafumi Kanamori, Klaus-Robert Müller, Sam Roweis, Neil Rubens, Tobias Scheffer, Marcel Schmittfull, Bernhard Schölkopf Hidetoshi Shimodaira, Alex Smola, Amos Storkey, Masashi Sugiyama

Domain Adaptation in Computer Vision Applications

Domain Adaptation in Computer Vision Applications
  • Author : Gabriela Csurka
  • Publisher :Unknown
  • Release Date :2018-06-28
  • Total pages :229
  • ISBN : 3319863835
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Summary : 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 data as well as deep architectures Presents a positioning of the dataset bias in the CNN-based feature arena Proposes detailed analyses of popular shallow methods that addresses landmark data selection, kernel embedding, feature alignment, joint feature transformation and classifier adaptation, or the case of limited access to the source data Discusses more recent deep DA methods, including discrepancy-based adaptation networks and adversarial discriminative DA models Addresses domain adaptation problems beyond image categorization, such as a Fisher encoding adaptation for vehicle re-identification, semantic segmentation and detection trained on synthetic images, and domain generalization for semantic part detection Describes a multi-source domain generalization technique for visual attributes and a unifying framework for multi-domain and multi-task learning This authoritative volume will be of great interest to a broad audience ranging from researchers and practitioners, to students involved in computer vision, pattern recognition and machine learning. Dr. Gabriela Csurka is a Senior Scientist in the Computer Vision Team at Xerox Research Centre Europe, Meylan, France.

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 :Unknown
  • Release Date :2007-08-30
  • Total pages :644
  • ISBN : 9783540749769
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Summary : 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 Archaeological Method and Theory

Advances in Archaeological Method and Theory
  • Author : Anonim
  • Publisher :Unknown
  • Release Date :2014-06-28
  • Total pages :455
  • ISBN : 9781483294285
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Summary : Advances in Archaeological Method and Theory

Advances in Connectionist and Neural Computation Theory

Advances in Connectionist and Neural Computation Theory
  • Author : Anonim
  • Publisher :Unknown
  • Release Date :1994
  • Total pages :229
  • ISBN : UOM:39076001449532
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Summary :

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 :Unknown
  • Release Date :2019-04-02
  • Total pages :392
  • ISBN : 9783030168414
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Summary : 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 addition to regular sessions, INNS BDDL welcomed around 40 oral communications, 6 tutorials have been presented together with 4 invited plenary speakers. This book covers a broad range of topics in big data and deep learning, from theoretical aspects to state-of-the-art applications. This book is directed to both Ph.D. students and Researchers in the field in order to provide a general picture of the state-of-the-art on the topics addressed by the conference.

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 :Unknown
  • Release Date :1992
  • Total pages :211
  • ISBN : 0262581116
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Summary : 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 :Unknown
  • Release Date :2012-09-26
  • Total pages :889
  • ISBN : 9783642337093
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Summary : 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 segmentation.

Person Re-Identification

Person Re-Identification
  • Author : Shaogang Gong,Marco Cristani,Shuicheng Yan,Chen Change Loy
  • Publisher :Unknown
  • Release Date :2014-01-03
  • Total pages :445
  • ISBN : 9781447162964
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Summary : 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 function and distance metric learning and discusses potential solutions to issues of data scalability and identity inference; investigates the limitations of existing benchmark datasets, presents strategies for camera topology inference and describes techniques for improving post-rank search efficiency; explores the design rationale and implementation considerations of building a practical re-identification system.

Advances in Case-Based Reasoning

Advances in Case-Based Reasoning
  • Author : France Ewcbr-9 1994 Chantilly,Jean-Paul Haton,Mark Keane,Michel Manago
  • Publisher :Unknown
  • Release Date :1995-10-11
  • Total pages :306
  • ISBN : 3540603646
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Summary : The type of material considered for publication includes drafts of original papers or monographs, technical reports of high quality and broad interest, advanced-level lectures, reports of meetings, provided they are of exceptional interest and focused on a single topic.

Machine Learning and Knowledge Discovery in Databases

Machine Learning and Knowledge Discovery in Databases
  • Author : Michelangelo Ceci,Jaakko Hollmén,Ljupčo Todorovski,Celine Vens,Sašo Džeroski
  • Publisher :Unknown
  • Release Date :2017-12-29
  • Total pages :866
  • ISBN : 9783319712468
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Summary : The three volume proceedings LNAI 10534 – 10536 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2017, held in Skopje, Macedonia, in September 2017. The total of 101 regular papers presented in part I and part II was carefully reviewed and selected from 364 submissions; there are 47 papers in the applied data science, nectar and demo track. The contributions were organized in topical sections named as follows: Part I: anomaly detection; computer vision; ensembles and meta learning; feature selection and extraction; kernel methods; learning and optimization, matrix and tensor factorization; networks and graphs; neural networks and deep learning. Part II: pattern and sequence mining; privacy and security; probabilistic models and methods; recommendation; regression; reinforcement learning; subgroup discovery; time series and streams; transfer and multi-task learning; unsupervised and semisupervised learning. Part III: applied data science track; nectar track; and demo track.

Adaptive Learning Methods for Nonlinear System Modeling

Adaptive Learning Methods for Nonlinear System Modeling
  • Author : Danilo Comminiello,Jose C. Principe
  • Publisher :Unknown
  • Release Date :2018-06-11
  • Total pages :388
  • ISBN : 9780128129777
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Summary : Adaptive Learning Methods for Nonlinear System Modeling presents some of the recent advances on adaptive algorithms and machine learning methods designed for nonlinear system modeling and identification. Real-life problems always entail a certain degree of nonlinearity, which makes linear models a non-optimal choice. This book mainly focuses on those methodologies for nonlinear modeling that involve any adaptive learning approaches to process data coming from an unknown nonlinear system. By learning from available data, such methods aim at estimating the nonlinearity introduced by the unknown system. In particular, the methods presented in this book are based on online learning approaches, which process the data example-by-example and allow to model even complex nonlinearities, e.g., showing time-varying and dynamic behaviors. Possible fields of applications of such algorithms includes distributed sensor networks, wireless communications, channel identification, predictive maintenance, wind prediction, network security, vehicular networks, active noise control, information forensics and security, tracking control in mobile robots, power systems, and nonlinear modeling in big data, among many others. This book serves as a crucial resource for researchers, PhD and post-graduate students working in the areas of machine learning, signal processing, adaptive filtering, nonlinear control, system identification, cooperative systems, computational intelligence. This book may be also of interest to the industry market and practitioners working with a wide variety of nonlinear systems. Presents the key trends and future perspectives in the field of nonlinear signal processing and adaptive learning. Introduces novel solutions and improvements over the state-of-the-art methods in the very exciting area of online and adaptive nonlinear identification. Helps readers understand important methods that are effective in nonlinear system modelling, suggesting the right methodology to address particular issues.

Advances in Case-Based Reasoning

Advances in Case-Based Reasoning
  • Author : Barry Smyth,EWCBR-98,Padraig Cunningham,P. Adradg Cunningham
  • Publisher :Unknown
  • Release Date :1998-09-09
  • Total pages :482
  • ISBN : 3540649905
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Summary : This book constitutes the refereed proceedings of the 4th European Workshop on Case-Based Reasoning, EWCBR-98, held in Dublin, Ireland, in September 1998. The 41 revised full papers presented were carefully selected and reviewed for inclusion in the proceedings. The contributions address the representation and organization of cases in case-bases, the assessment of case similarity, the efficient retrieval of cases from large case-bases, the adaptation of similar case solutions to fit the current problem, case learning and case-base maintenance, and the application of CBR technology to real-world problems.

Transfer Learning

Transfer Learning
  • Author : Qiang Yang,Yu Zhang,Wenyuan Dai,Sinno Jialin Pan
  • Publisher :Unknown
  • Release Date :2020-01-31
  • Total pages :393
  • ISBN : 9781107016903
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Summary : This in-depth tutorial for students, researchers, and developers covers foundations, plus applications ranging from search to multimedia.

Urban Sustainability in Theory and Practice

Urban Sustainability in Theory and Practice
  • Author : Paul James
  • Publisher :Unknown
  • Release Date :2014-09-19
  • Total pages :260
  • ISBN : 9781317658351
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Summary : Cities are home to the most consequential current attempts at human adaptation and they provide one possible focus for the flourishing of life on this planet. However, for this to be realized in more than an ad hoc way, a substantial rethinking of current approaches and practices needs to occur. Urban Sustainability in Theory and Practice responds to the crises of sustainability in the world today by going back to basics. It makes four major contributions to thinking about and acting upon cities. It provides a means of reflexivity learning about urban sustainability in the process of working practically for positive social development and projected change. It challenges the usually taken-for-granted nature of sustainability practices while providing tools for modifying those practices. It emphasizes the necessity of a holistic and integrated understanding of urban life. Finally it rewrites existing dominant understandings of the social whole such as the triple-bottom line approach that reduce environmental questions to externalities and social questions to background issues. The book is a much-needed practical and conceptual guide for rethinking urban engagement. Covering the full range of sustainability domains and bridging discourses aimed at academics and practitioners, this is an essential read for all those studying, researching and working in urban geography, sustainability assessment, urban planning, urban sociology and politics, sustainable development and environmental studies.

Advances in Circuits and Systems

Advances in Circuits and Systems
  • Author : Anonim
  • Publisher :Unknown
  • Release Date :1985
  • Total pages :549
  • ISBN : UOM:39015009817217
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Summary :

Advances in Information Retrieval

Advances in Information Retrieval
  • Author : Mohand Boughanem,Catherine Berrut,Josiane Mothe,Chantal Soule-Dupuy
  • Publisher :Unknown
  • Release Date :2009-03-27
  • Total pages :821
  • ISBN : 9783642009570
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Summary : This book constitutes the refereed proceedings of the 30th annual European Conference on Information Retrieval Research, ECIR 2009, held in Toulouse, France in April 2009. The 42 revised full papers and 18 revised short papers presented together with the abstracts of 3 invited lectures and 25 poster papers were carefully reviewed and selected from 188 submissions. The papers are organized in topical sections on retrieval model, collaborative IR / filtering, learning, multimedia - metadata, expert search - advertising, evaluation, opinion detection, web IR, representation, clustering / categorization as well as distributed IR.