Theory Of Disagreement Based Active Learning
DOWNLOAD
Download Theory Of Disagreement Based Active Learning PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Theory Of Disagreement Based Active Learning book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Theory Of Disagreement Based Active Learning
DOWNLOAD
Author : Steve Hanneke
language : en
Publisher:
Release Date : 2014
Theory Of Disagreement Based Active Learning written by Steve Hanneke and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Machine learning categories.
Active learning is a protocol for supervised machine learning, in which a learning algorithm sequentially requests the labels of selected data points from a large pool of unlabeled data. This contrasts with passive learning, where the labeled data are taken at random. The objective in active learning is to produce a highly-accurate classifier, ideally using fewer labels than the number of random labeled data sufficient for passive learning to achieve the same. This article describes recent advances in our understanding of the theoretical benefits of active learning, and implications for the design of effective active learning algorithms. Much of the article focuses on a particular technique, namely disagreement-based active learning, which by now has amassed a mature and coherent literature. It also briefly surveys several alternative approaches from the literature. The emphasis is on theorems regarding the performance of a few general algorithms, including rigorous proofs where appropriate. However, the presentation is intended to be pedagogical, focusing on results that illustrate fundamental ideas, rather than obtaining the strongest or most general known theorems. The intended audience includes researchers and advanced graduate students in machine learning and statistics, interested in gaining a deeper understanding of the recent and ongoing developments in the theory of active learning.
Active Learning
DOWNLOAD
Author : Burr Settles
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2012-07-01
Active Learning written by Burr Settles and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-07-01 with Computers categories.
The key idea behind active learning is that a machine learning algorithm can perform better with less training if it is allowed to choose the data from which it learns. An active learner may pose "queries," usually in the form of unlabeled data instances to be labeled by an "oracle" (e.g., a human annotator) that already understands the nature of the problem. This sort of approach is well-motivated in many modern machine learning and data mining applications, where unlabeled data may be abundant or easy to come by, but training labels are difficult, time-consuming, or expensive to obtain. This book is a general introduction to active learning. It outlines several scenarios in which queries might be formulated, and details many query selection algorithms which have been organized into four broad categories, or "query selection frameworks." We also touch on some of the theoretical foundations of active learning, and conclude with an overview of the strengths and weaknesses of these approaches in practice, including a summary of ongoing work to address these open challenges and opportunities. Table of Contents: Automating Inquiry / Uncertainty Sampling / Searching Through the Hypothesis Space / Minimizing Expected Error and Variance / Exploiting Structure in Data / Theory / Practical Considerations
Algorithmic Learning Theory
DOWNLOAD
Author : Ronald Ortner
language : en
Publisher: Springer
Release Date : 2016-10-12
Algorithmic Learning Theory written by Ronald Ortner and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-12 with Computers categories.
This book constitutes the refereed proceedings of the 27th International Conference on Algorithmic Learning Theory, ALT 2016, held in Bari, Italy, in October 2016, co-located with the 19th International Conference on Discovery Science, DS 2016. The 24 regular papers presented in this volume were carefully reviewed and selected from 45 submissions. In addition the book contains 5 abstracts of invited talks. The papers are organized in topical sections named: error bounds, sample compression schemes; statistical learning, theory, evolvability; exact and interactive learning; complexity of teaching models; inductive inference; online learning; bandits and reinforcement learning; and clustering.
Inductive Logic Programming
DOWNLOAD
Author : Fabrizio Riguzzi
language : en
Publisher: Springer
Release Date : 2018-08-24
Inductive Logic Programming written by Fabrizio Riguzzi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-24 with Computers categories.
This book constitutes the refereed conference proceedings of the 28th International Conference on Inductive Logic Programming, ILP 2018, held in Ferrara, Italy, in September 2018. The 10 full papers presented were carefully reviewed and selected from numerous submissions. Inductive Logic Programming (ILP) is a subfield of machine learning, which originally relied on logic programming as a uniform representation language for expressing examples, background knowledge and hypotheses. Due to its strong representation formalism, based on first-order logic, ILP provides an excellent means for multi-relational learning and data mining, and more generally for learning from structured data.
Pattern Recognition And Image Analysis
DOWNLOAD
Author : Armando J. Pinho
language : en
Publisher: Springer Nature
Release Date : 2022-04-25
Pattern Recognition And Image Analysis written by Armando J. Pinho and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-25 with Computers categories.
This book constitutes the refereed proceedings of the 10th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2022, held in Aveiro, Portugal, in May 2022. The 54 papers accepted for these proceedings were carefully reviewed and selected from 72 submissions. They deal with document analysis; medical image processing; biometrics; pattern recognition and machine learning; computer vision; and other applications.
Ethics Of Artificial Intelligence
DOWNLOAD
Author : S. Matthew Liao
language : en
Publisher: Oxford University Press
Release Date : 2020-08-18
Ethics Of Artificial Intelligence written by S. Matthew Liao and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-18 with Philosophy categories.
As Artificial Intelligence (AI) technologies rapidly progress, questions about the ethics of AI, in both the near-future and the long-term, become more pressing than ever. This volume features seventeen original essays by prominent AI scientists and philosophers and represents the state-of-the-art thinking in this fast-growing field. Organized into four sections, this volume explores the issues surrounding how to build ethics into machines; ethical issues in specific technologies, including self-driving cars, autonomous weapon systems, surveillance algorithms, and sex robots; the long term risks of superintelligence; and whether AI systems can be conscious or have rights. Though the use and practical applications of AI are growing exponentially, discussion of its ethical implications is still in its infancy. This volume provides an invaluable resource for thinking through the ethical issues surrounding AI today and for shaping the study and development of AI in the coming years.
Algorithmic Learning Theory
DOWNLOAD
Author : Kamalika Chaudhuri
language : en
Publisher: Springer
Release Date : 2015-10-04
Algorithmic Learning Theory written by Kamalika Chaudhuri and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-04 with Computers categories.
This book constitutes the proceedings of the 26th International Conference on Algorithmic Learning Theory, ALT 2015, held in Banff, AB, Canada, in October 2015, and co-located with the 18th International Conference on Discovery Science, DS 2015. The 23 full papers presented in this volume were carefully reviewed and selected from 44 submissions. In addition the book contains 2 full papers summarizing the invited talks and 2 abstracts of invited talks. The papers are organized in topical sections named: inductive inference; learning from queries, teaching complexity; computational learning theory and algorithms; statistical learning theory and sample complexity; online learning, stochastic optimization; and Kolmogorov complexity, algorithmic information theory.
Computer Vision Eccv 2022 Workshops
DOWNLOAD
Author : Leonid Karlinsky
language : en
Publisher: Springer Nature
Release Date : 2023-02-11
Computer Vision Eccv 2022 Workshops written by Leonid Karlinsky and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-11 with Computers categories.
The 8-volume set, comprising the LNCS books 13801 until 13809, constitutes the refereed proceedings of 38 out of the 60 workshops held at the 17th European Conference on Computer Vision, ECCV 2022. The conference took place in Tel Aviv, Israel, during October 23-27, 2022; the workshops were held hybrid or online. The 367 full papers included in this volume set were carefully reviewed and selected for inclusion in the ECCV 2022 workshop proceedings. They were organized in individual parts as follows: Part I: W01 - AI for Space; W02 - Vision for Art; W03 - Adversarial Robustness in the Real World; W04 - Autonomous Vehicle Vision Part II: W05 - Learning With Limited and Imperfect Data; W06 - Advances in Image Manipulation; Part III: W07 - Medical Computer Vision; W08 - Computer Vision for Metaverse; W09 - Self-Supervised Learning: What Is Next?; Part IV: W10 - Self-Supervised Learning for Next-Generation Industry-Level Autonomous Driving; W11 - ISIC Skin Image Analysis; W12 - Cross-Modal Human-Robot Interaction; W13 - Text in Everything; W14 - BioImage Computing; W15 - Visual Object-Oriented Learning Meets Interaction: Discovery, Representations, and Applications; W16 - AI for Creative Video Editing and Understanding; W17 - Visual Inductive Priors for Data-Efficient Deep Learning; W18 - Mobile Intelligent Photography and Imaging; Part V: W19 - People Analysis: From Face, Body and Fashion to 3D Virtual Avatars; W20 - Safe Artificial Intelligence for Automated Driving; W21 - Real-World Surveillance: Applications and Challenges; W22 - Affective Behavior Analysis In-the-Wild; Part VI: W23 - Visual Perception for Navigation in Human Environments: The JackRabbot Human Body Pose Dataset and Benchmark; W24 - Distributed Smart Cameras; W25 - Causality in Vision; W26 - In-Vehicle Sensing and Monitorization; W27 - Assistive Computer Vision and Robotics; W28 - Computational Aspects of Deep Learning; Part VII: W29 - Computer Vision for Civil and Infrastructure Engineering; W30 - AI-Enabled Medical Image Analysis: Digital Pathology and Radiology/COVID19; W31 - Compositional and Multimodal Perception; Part VIII: W32 - Uncertainty Quantification for Computer Vision; W33 - Recovering 6D Object Pose; W34 - Drawings and Abstract Imagery: Representation and Analysis; W35 - Sign Language Understanding; W36 - A Challenge for Out-of-Distribution Generalization in Computer Vision; W37 - Vision With Biased or Scarce Data; W38 - Visual Object Tracking Challenge.
Theory And Practice Of Active Learning
DOWNLOAD
Author : Ron Begleiter
language : en
Publisher:
Release Date : 2013
Theory And Practice Of Active Learning written by Ron Begleiter and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with categories.
Artificial Neural Networks And Machine Learning Icann 2019 Workshop And Special Sessions
DOWNLOAD
Author : Igor V. Tetko
language : en
Publisher: Springer Nature
Release Date : 2019-09-10
Artificial Neural Networks And Machine Learning Icann 2019 Workshop And Special Sessions written by Igor V. Tetko and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-10 with Computers categories.
The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions.