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Author: Nada Lavrač Publisher: Springer Science & Business Media ISBN: 3540201211 Category : Computers Languages : en Pages : 521
Book Description
This book constitutes the refereed proceedings of the 14th European Conference on Machine Learning, ECML 2003, held in Cavtat-Dubrovnik, Croatia in September 2003 in conjunction with PKDD 2003. The 40 revised full papers presented together with 4 invited contributions were carefully reviewed and, together with another 40 ones for PKDD 2003, selected from a total of 332 submissions. The papers address all current issues in machine learning including support vector machine, inductive inference, feature selection algorithms, reinforcement learning, preference learning, probabilistic grammatical inference, decision tree learning, clustering, classification, agent learning, Markov networks, boosting, statistical parsing, Bayesian learning, supervised learning, and multi-instance learning.
Author: Nada Lavrač Publisher: Springer Science & Business Media ISBN: 3540201211 Category : Computers Languages : en Pages : 521
Book Description
This book constitutes the refereed proceedings of the 14th European Conference on Machine Learning, ECML 2003, held in Cavtat-Dubrovnik, Croatia in September 2003 in conjunction with PKDD 2003. The 40 revised full papers presented together with 4 invited contributions were carefully reviewed and, together with another 40 ones for PKDD 2003, selected from a total of 332 submissions. The papers address all current issues in machine learning including support vector machine, inductive inference, feature selection algorithms, reinforcement learning, preference learning, probabilistic grammatical inference, decision tree learning, clustering, classification, agent learning, Markov networks, boosting, statistical parsing, Bayesian learning, supervised learning, and multi-instance learning.
Author: Johannes Fürnkranz Publisher: Springer Science & Business Media ISBN: 3642141250 Category : Computers Languages : en Pages : 457
Book Description
The topic of preferences is a new branch of machine learning and data mining, and it has attracted considerable attention in artificial intelligence research in previous years. It involves learning from observations that reveal information about the preferences of an individual or a class of individuals. Representing and processing knowledge in terms of preferences is appealing as it allows one to specify desires in a declarative way, to combine qualitative and quantitative modes of reasoning, and to deal with inconsistencies and exceptions in a flexible manner. And, generalizing beyond training data, models thus learned may be used for preference prediction. This is the first book dedicated to this topic, and the treatment is comprehensive. The editors first offer a thorough introduction, including a systematic categorization according to learning task and learning technique, along with a unified notation. The first half of the book is organized into parts on label ranking, instance ranking, and object ranking; while the second half is organized into parts on applications of preference learning in multiattribute domains, information retrieval, and recommender systems. The book will be of interest to researchers and practitioners in artificial intelligence, in particular machine learning and data mining, and in fields such as multicriteria decision-making and operations research.
Author: Jean-Francois Boulicaut Publisher: Springer Science & Business Media ISBN: 3540231056 Category : Computers Languages : en Pages : 597
Book Description
This book constitutes the refereed proceedings of the 15th European Conference on Machine Learning, ECML 2004, held in Pisa, Italy, in September 2004, jointly with PKDD 2004. The 45 revised full papers and 6 revised short papers presented together with abstracts of 5 invited talks were carefully reviewed and selected from 280 papers submitted to ECML and 107 papers submitted to both, ECML and PKDD. The papers present a wealth of new results in the area and address all current issues in machine learning.
Author: Peter Flach Publisher: Cambridge University Press ISBN: 1107096391 Category : Computers Languages : en Pages : 415
Book Description
Covering all the main approaches in state-of-the-art machine learning research, this will set a new standard as an introductory textbook.
Author: João Gama Publisher: Springer Science & Business Media ISBN: 3540292438 Category : Computers Languages : en Pages : 784
Book Description
This book constitutes the refereed proceedings of the 16th European Conference on Machine Learning, ECML 2005, jointly held with PKDD 2005 in Porto, Portugal, in October 2005. The 40 revised full papers and 32 revised short papers presented together with abstracts of 6 invited talks were carefully reviewed and selected from 335 papers submitted to ECML and 30 papers submitted to both, ECML and PKDD. The papers present a wealth of new results in the area and address all current issues in machine learning.
Author: Joost N. Kok Publisher: Springer Science & Business Media ISBN: 3540749578 Category : Computers Languages : en Pages : 829
Book Description
This book constitutes the refereed proceedings of the 18th European Conference on Machine Learning, ECML 2007, held in Warsaw, Poland, September 2007, jointly with PKDD 2007. The 41 revised full papers and 37 revised short papers presented together with abstracts of four invited talks were carefully reviewed and selected from 592 abstracts submitted to both, ECML and PKDD. The papers present a wealth of new results in the area and address all current issues in machine learning.
Author: Mihai Dascălu Publisher: Springer ISBN: 3319034197 Category : Technology & Engineering Languages : en Pages : 283
Book Description
With the advent and increasing popularity of Computer Supported Collaborative Learning (CSCL) and e-learning technologies, the need of automatic assessment and of teacher/tutor support for the two tightly intertwined activities of comprehension of reading materials and of collaboration among peers has grown significantly. In this context, a polyphonic model of discourse derived from Bakhtin’s work as a paradigm is used for analyzing both general texts and CSCL conversations in a unique framework focused on different facets of textual cohesion. As specificity of our analysis, the individual learning perspective is focused on the identification of reading strategies and on providing a multi-dimensional textual complexity model, whereas the collaborative learning dimension is centered on the evaluation of participants’ involvement, as well as on collaboration assessment. Our approach based on advanced Natural Language Processing techniques provides a qualitative estimation of the learning process and enhances understanding as a “mediator of learning” by providing automated feedback to both learners and teachers or tutors. The main benefits are its flexibility, extensibility and nevertheless specificity for covering multiple stages, starting from reading classroom materials, to discussing on specific topics in a collaborative manner and finishing the feedback loop by verbalizing metacognitive thoughts.
Author: Obaid, Ahmed J. Publisher: IGI Global ISBN: 1668460629 Category : Computers Languages : en Pages : 409
Book Description
In recent years, falsification and digital modification of video clips, images, as well as textual contents have become widespread and numerous, especially when deepfake technologies are adopted in many sources. Due to adopted deepfake techniques, a lot of content currently cannot be recognized from its original sources. As a result, the field of study previously devoted to general multimedia forensics has been revived. The Handbook of Research on Advanced Practical Approaches to Deepfake Detection and Applications discusses the recent techniques and applications of illustration, generation, and detection of deepfake content in multimedia. It introduces the techniques and gives an overview of deepfake applications, types of deepfakes, the algorithms and applications used in deepfakes, recent challenges and problems, and practical applications to identify, generate, and detect deepfakes. Covering topics such as anomaly detection, intrusion detection, and security enhancement, this major reference work is a comprehensive resource for cyber security specialists, government officials, law enforcement, business leaders, students and faculty of higher education, librarians, researchers, and academicians.
Author: Publisher: Elsevier ISBN: 0444640436 Category : Mathematics Languages : en Pages : 540
Book Description
Computational Analysis and Understanding of Natural Languages: Principles, Methods and Applications, Volume 38, the latest release in this monograph that provides a cohesive and integrated exposition of these advances and associated applications, includes new chapters on Linguistics: Core Concepts and Principles, Grammars, Open-Source Libraries, Application Frameworks, Workflow Systems, Mathematical Essentials, Probability, Inference and Prediction Methods, Random Processes, Bayesian Methods, Machine Learning, Artificial Neural Networks for Natural Language Processing, Information Retrieval, Language Core Tasks, Language Understanding Applications, and more. The synergistic confluence of linguistics, statistics, big data, and high-performance computing is the underlying force for the recent and dramatic advances in analyzing and understanding natural languages, hence making this series all the more important. - Provides a thorough treatment of open-source libraries, application frameworks and workflow systems for natural language analysis and understanding - Presents new chapters on Linguistics: Core Concepts and Principles, Grammars, Open-Source Libraries, Application Frameworks, Workflow Systems, Mathematical Essentials, Probability, and more
Author: Nada Lavrač
Author: Nada Lavrač
Author: Nada Lavra
Author: Johannes Fürnkranz
Author: Jean-Francois Boulicaut
Author: Peter Flach
Author: João Gama
Author: Joost N. Kok
Author: Mihai Dascălu
Author: Obaid, Ahmed J.
Author: