New Perspectives In Neural Architecture Search
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New Perspectives In Neural Architecture Search
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Author : Shen Yan
language : en
Publisher:
Release Date : 2022
New Perspectives In Neural Architecture Search written by Shen Yan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Electronic dissertations categories.
Neural architecture search (NAS) has made significant strides in recent years, but challenges remain in terms of the stability of search performance and the high computational requirements of sampling-based NAS. Studying architecture representations offers a promising solution to these challenges, as it encourages neural architectures with similar structures or computations to cluster together. This helps to map neural architectures with similar performance to the same regions in the latent space and leads to smoother transitions in the latent space, benefiting downstream search. Additionally, learning curve extrapolation can accelerate the search process by estimating the final validation accuracy of a neural network from the learning curve of a partially trained network. Overall, understanding the neural architecture representations and their associated learning curves through theoretical analysis and empirical evaluations is crucial for achieving stable and scalable NAS.This dissertation presents our contributions to the field of neural architecture search (NAS), which push the limits of NAS and achieve state-of-the-art performance. Our contributions include efficient one-shot NAS via hierarchical masking, addressing the joint optimization problem of architecture representations and search through unsupervised pre-training, improving the generalization ability of architecture representations with computation-aware self-supervised training, and developing a method for facilitating multi-fidelity NAS research.
Automated Machine Learning
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Author : Frank Hutter
language : en
Publisher: Springer
Release Date : 2019-05-17
Automated Machine Learning written by Frank Hutter and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-17 with Computers categories.
This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML methods that can be used easily and without expert knowledge. However, many of the recent machine learning successes crucially rely on human experts, who manually select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. To overcome this problem, the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself. This book serves as a point of entry into this quickly-developing field for researchers and advanced students alike, as well as providing a reference for practitioners aiming to use AutoML in their work.
New Perspectives On Hybrid Intelligent System Design Based On Fuzzy Logic Neural Networks And Metaheuristics
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Author : Oscar Castillo
language : en
Publisher: Springer Nature
Release Date : 2022-09-30
New Perspectives On Hybrid Intelligent System Design Based On Fuzzy Logic Neural Networks And Metaheuristics written by Oscar Castillo and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-30 with Technology & Engineering categories.
In this book, recent developments on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, are presented. In addition, the above-mentioned methods are applied to areas such as, intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. The book contains a collection of papers focused on hybrid intelligent systems based on soft computing techniques. There are some papers with the main theme of type-1 and type-2 fuzzy logic, which basically consists of papers that propose new concepts and algorithms based on type-1 and type-2 fuzzy logic and their applications. There also some papers that offer theoretical concepts and applications of meta-heuristics in different areas. Another group of papers describe diverse applications of fuzzy logic, neural networks and hybrid intelligent systems in medical problems. There are also some papers that present theory and practice of neural networks in different areas of application. In addition, there are papers that present theory and practice of optimization and evolutionary algorithms in different areas of application. Finally, there are some papers describing applications of fuzzy logic, neural networks and meta-heuristics in pattern recognition and classification problems.
Evolutionary Deep Neural Architecture Search Fundamentals Methods And Recent Advances
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Author : Yanan Sun
language : en
Publisher: Springer Nature
Release Date : 2022-11-08
Evolutionary Deep Neural Architecture Search Fundamentals Methods And Recent Advances written by Yanan Sun and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-08 with Technology & Engineering categories.
This book systematically narrates the fundamentals, methods, and recent advances of evolutionary deep neural architecture search chapter by chapter. This will provide the target readers with sufficient details learning from scratch. In particular, the method parts are devoted to the architecture search of unsupervised and supervised deep neural networks. The people, who would like to use deep neural networks but have no/limited expertise in manually designing the optimal deep architectures, will be the main audience. This may include the researchers who focus on developing novel evolutionary deep architecture search methods for general tasks, the students who would like to study the knowledge related to evolutionary deep neural architecture search and perform related research in the future, and the practitioners from the fields of computer vision, natural language processing, and others where the deep neural networks have been successfully and largely used in their respective fields.
Good Practices And New Perspectives In Information Systems And Technologies
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Author : Álvaro Rocha
language : en
Publisher: Springer Nature
Release Date :
Good Practices And New Perspectives In Information Systems And Technologies written by Álvaro Rocha and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Computer Vision Eccv 2020
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Author : Andrea Vedaldi
language : en
Publisher: Springer Nature
Release Date : 2020-11-15
Computer Vision Eccv 2020 written by Andrea Vedaldi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-15 with Computers categories.
The 30-volume set, comprising the LNCS books 12346 until 12375, constitutes the refereed proceedings of the 16th European Conference on Computer Vision, ECCV 2020, which was planned to be held in Glasgow, UK, during August 23-28, 2020. The conference was held virtually due to the COVID-19 pandemic. The 1360 revised papers presented in these proceedings were carefully reviewed and selected from a total of 5025 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.
Efficient And Practical Neural Architecture Search
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Author : Thomas Elsken
language : en
Publisher:
Release Date : 2021
Efficient And Practical Neural Architecture Search written by Thomas Elsken and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
Computer Vision Eccv 2022
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Author : Shai Avidan
language : en
Publisher: Springer Nature
Release Date : 2022-11-10
Computer Vision Eccv 2022 written by Shai Avidan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-10 with Computers categories.
The 39-volume set, comprising the LNCS books 13661 until 13699, constitutes the refereed proceedings of the 17th European Conference on Computer Vision, ECCV 2022, held in Tel Aviv, Israel, during October 23–27, 2022. The 1645 papers presented in these proceedings were carefully reviewed and selected from a total of 5804 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.
Computer Vision Accv 2020
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Author : Hiroshi Ishikawa
language : en
Publisher: Springer Nature
Release Date : 2021-02-24
Computer Vision Accv 2020 written by Hiroshi Ishikawa and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-24 with Computers categories.
The six volume set of LNCS 12622-12627 constitutes the proceedings of the 15th Asian Conference on Computer Vision, ACCV 2020, held in Kyoto, Japan, in November/ December 2020.* The total of 254 contributions was carefully reviewed and selected from 768 submissions during two rounds of reviewing and improvement. The papers focus on the following topics: Part I: 3D computer vision; segmentation and grouping Part II: low-level vision, image processing; motion and tracking Part III: recognition and detection; optimization, statistical methods, and learning; robot vision Part IV: deep learning for computer vision, generative models for computer vision Part V: face, pose, action, and gesture; video analysis and event recognition; biomedical image analysis Part VI: applications of computer vision; vision for X; datasets and performance analysis *The conference was held virtually.
Neural Architecture Search For Dense Prediction Tasks In Computer Vision
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Author : Rohit Mohan
language : en
Publisher:
Release Date : 2023
Neural Architecture Search For Dense Prediction Tasks In Computer Vision written by Rohit Mohan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.
Abstract: The success of deep learning in recent years has lead to a rising demand for neural network architecture engineering. As a consequence, neural architecture search (NAS), which aims at automatically designing neural network architectures in a data-driven manner rather than manually, has evolved as a popular field of research. With the advent of weight sharing strategies across architectures, NAS has become applicable to a much wider range of problems. In particular, there are now many publications for dense prediction tasks in computer vision that require pixel-level predictions, such as semantic segmentation or object detection. These tasks come with novel challenges, such as higher memory footprints due to high-resolution data, learning multi-scale representations, longer training times, and more complex and larger neural architectures. In this manuscript, we provide an overview of NAS for dense prediction tasks by elaborating on these novel challenges and surveying ways to address them to ease future research and application of existing methods to novel problems
