Download or read book Convex Relaxation for Low dimensional Representation written by Samet Oymak and published by . This book was released on 2015 with total page 588 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is a growing interest in taking advantage of possible patterns and structures in data so as to extract the desired information and overcome the curse of dimensionality. In a wide range of applications, including computer vision, machine learning, medical imaging, and social networks, the signal that gives rise to the observations can be modeled to be approximately sparse and exploiting this fact can be very beneficial. This has led to an immense interest in the problem of efficiently reconstructing a sparse signal from limited linear observations. More recently, low-rank approximation techniques have become prominent tools to approach problems arising in machine learning, system identification and quantum tomography. In sparse and low-rank estimation problems, the challenge is the inherent intractability of the objective function, and one needs efficient methods to capture the low-dimensionality of these models. Convex optimization is often a promising tool to attack such problems. An intractable problem with a combinatorial objective can often be "relaxed" to obtain a tractable but almost as powerful convex optimization problem. This dissertation studies convex optimization techniques that can take advantage of low-dimensional representations of the underlying high-dimensional data. We provide provable guarantees that ensure that the proposed algorithms will succeed under reasonable conditions, and answer questions of the following flavor: For a given number of measurements, can we reliably estimate the true signal? If so, how good is the reconstruction as a function of the model parameters? More specifically, i) Focusing on linear inverse problems, we generalize the classical error bounds known for the least-squares technique to the lasso formulation, which incorporates the signal model. ii) We show that intuitive convex approaches do not perform as well as expected when it comes to signals that have multiple low-dimensional structures simultaneously. iii) Finally, we propose convex relaxations for the graph clustering problem and give sharp performance guarantees for a family of graphs arising from the so-called stochastic block model. We pay particular attention to the following aspects. For i) and ii), we aim to provide a general geometric framework, in which the results on sparse and low-rank estimation can be obtained as special cases. For i) and iii), we investigate the precise performance characterization, which yields the right constants in our bounds and the true dependence between the problem parameters.
Download or read book High Dimensional Data Analysis with Low Dimensional Models written by John Wright and published by Cambridge University Press. This book was released on 2022-01-13 with total page 717 pages. Available in PDF, EPUB and Kindle. Book excerpt: Connects fundamental mathematical theory with real-world problems, through efficient and scalable optimization algorithms.
Download or read book Integer Programming and Combinatorial Optimization written by Michel Goemans and published by Springer. This book was released on 2013-03-12 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 16th International Conference on Integer Programming and Combinatorial Optimization, IPCO 2013, held in Valparaíso, Chile, in March 2013. The 33 full papers presented were carefully reviewed and selected from 98 submissions. The conference is a forum for researchers and practitioners working on various aspects of integer programming and combinatorial optimization with the aim to present recent developments in theory, computation, and applications. The scope of IPCO is viewed in a broad sense, to include algorithmic and structural results in integer programming and combinatorial optimization as well as revealing computational studies and novel applications of discrete optimization to practical problems.
Download or read book Neural Advances in Processing Nonlinear Dynamic Signals written by Anna Esposito and published by Springer. This book was released on 2018-07-21 with total page 313 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book proposes neural networks algorithms and advanced machine learning techniques for processing nonlinear dynamic signals such as audio, speech, financial signals, feedback loops, waveform generation, filtering, equalization, signals from arrays of sensors, and perturbations in the automatic control of industrial production processes. It also discusses the drastic changes in financial, economic, and work processes that are currently being experienced by the computational and engineering sciences community. Addresses key aspects, such as the integration of neural algorithms and procedures for the recognition, the analysis and detection of dynamic complex structures and the implementation of systems for discovering patterns in data, the book highlights the commonalities between computational intelligence (CI) and information and communications technologies (ICT) to promote transversal skills and sophisticated processing techniques. This book is a valuable resource for a. The academic research community b. The ICT market c. PhD students and early stage researchers d. Companies, research institutes e. Representatives from industry and standardization bodies
Download or read book Intelligent Computing Theories and Application written by De-Shuang Huang and published by Springer. This book was released on 2016-07-11 with total page 924 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set LNCS 9771 and LNCS 9772 constitutes - in conjunction with the volume LNAI 9773 - the refereed proceedings of the 12th International Conference on Intelligent Computing, ICIC 2016, held in Lanzhou, China, in August 2016. The 221 full papers and 15 short papers of the three proceedings volumes were carefully reviewed and selected from 639 submissions. The papers are organized in topical sections such as signal processing and image processing; information security, knowledge discovery, and data mining; systems biology and intelligent computing in computational biology; intelligent computing in scheduling; information security; advances in swarm intelligence: algorithms and applications; machine learning and data analysis for medical and engineering applications; evolutionary computation and learning; independent component analysis; compressed sensing, sparse coding; social computing; neural networks; nature inspired computing and optimization; genetic algorithms; signal processing; pattern recognition; biometrics recognition; image processing; information security; virtual reality and human-computer interaction; healthcare informatics theory and methods; artificial bee colony algorithms; differential evolution; memetic algorithms; swarm intelligence and optimization; soft computing; protein structure and function prediction; advances in swarm intelligence: algorithms and applications; optimization, neural network, and signal processing; biomedical informatics and image processing; machine learning; knowledge discovery and natural language processing; nature inspired computing and optimization; intelligent control and automation; intelligent data analysis and prediction; computer vision; knowledge representation and expert system; bioinformatics.
Download or read book Modern Machine Learning Techniques and Their Applications in Cartoon Animation Research written by Jun Yu and published by John Wiley & Sons. This book was released on 2013-03-18 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: The integration of machine learning techniques and cartoon animation research is fast becoming a hot topic. This book helps readers learn the latest machine learning techniques, including patch alignment framework; spectral clustering, graph cuts, and convex relaxation; ensemble manifold learning; multiple kernel learning; multiview subspace learning; and multiview distance metric learning. It then presents the applications of these modern machine learning techniques in cartoon animation research. With these techniques, users can efficiently utilize the cartoon materials to generate animations in areas such as virtual reality, video games, animation films, and sport simulations
Download or read book Recent Advances in Optimization and its Applications in Engineering written by Moritz Diehl and published by Springer Science & Business Media. This book was released on 2010-09-21 with total page 535 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical optimization encompasses both a rich and rapidly evolving body of fundamental theory, and a variety of exciting applications in science and engineering. The present book contains a careful selection of articles on recent advances in optimization theory, numerical methods, and their applications in engineering. It features in particular new methods and applications in the fields of optimal control, PDE-constrained optimization, nonlinear optimization, and convex optimization. The authors of this volume took part in the 14th Belgian-French-German Conference on Optimization (BFG09) organized in Leuven, Belgium, on September 14-18, 2009. The volume contains a selection of reviewed articles contributed by the conference speakers as well as three survey articles by plenary speakers and two papers authored by the winners of the best talk and best poster prizes awarded at BFG09. Researchers and graduate students in applied mathematics, computer science, and many branches of engineering will find in this book an interesting and useful collection of recent ideas on the methods and applications of optimization.
Download or read book Design Studies and Intelligence Engineering written by L.C. Jain and published by IOS Press. This book was released on 2022-03-30 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: The technologies applied in design studies vary from basic theories to more application-based systems, and intelligence engineering technologies – such as computer-aided industrial design, human factor design, and greenhouse design – play a significant role in design science. Intelligence engineering technologies encompass both theoretical and application perspectives, such as computational technologies, sensing technologies, and video detection. Intelligence engineering is multidisciplinary in nature, promoting cooperation, exchange and discussion between organizations and researchers from diverse fields. This book presents the proceedings of DSIE2021, the 2021 International Symposium on Design Studies and Intelligence Engineering, held in Hangzhou, China, on 27 & 28 November 2021. This annual conference invites renowned experts from around the world to speak on their specialist topics, providing a platform for many professionals and researchers from industry and academia to exchange and discuss recent advances in the field of design studies and intelligence engineering. The 210 submissions received were rigorously reviewed, and each of the 50 papers presented here was selected based on scores from three or four referees. Papers cover a very wide range of topics, from the design of a pneumatic soft finger with two joints, and the emotion of texture, to the design evaluation of a health management terminal for the elderly, and a multi-robot planning algorithm with quad tree map division for obstacles of irregular shape. Providing a varied overview of recent developments in design and intelligence engineering, this book will be of interest to researchers and all those working in the field.
Download or read book Computer Vision ECCV 2010 written by Kostas Daniilidis and published by Springer. This book was released on 2010-09-24 with total page 833 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 2010 edition of the European Conference on Computer Vision was held in Heraklion, Crete. The call for papers attracted an absolute record of 1,174 submissions. We describe here the selection of the accepted papers: Thirty-eight area chairs were selected coming from Europe (18), USA and Canada (16), and Asia (4). Their selection was based on the following criteria: (1) Researchers who had served at least two times as Area Chairs within the past two years at major vision conferences were excluded; (2) Researchers who served as Area Chairs at the 2010 Computer Vision and Pattern Recognition were also excluded (exception: ECCV 2012 Program Chairs); (3) Minimization of overlap introduced by Area Chairs being former student and advisors; (4) 20% of the Area Chairs had never served before in a major conference; (5) The Area Chair selection process made all possible efforts to achieve a reasonable geographic distribution between countries, thematic areas and trends in computer vision. Each Area Chair was assigned by the Program Chairs between 28–32 papers. Based on paper content, the Area Chair recommended up to seven potential reviewers per paper. Such assignment was made using all reviewers in the database including the conflicting ones. The Program Chairs manually entered the missing conflict domains of approximately 300 reviewers. Based on the recommendation of the Area Chairs, three reviewers were selected per paper (with at least one being of the top three suggestions), with 99.
Download or read book Graph Embedding for Pattern Analysis written by Yun Fu and published by Springer Science & Business Media. This book was released on 2012-11-19 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: Graph Embedding for Pattern Recognition covers theory methods, computation, and applications widely used in statistics, machine learning, image processing, and computer vision. This book presents the latest advances in graph embedding theories, such as nonlinear manifold graph, linearization method, graph based subspace analysis, L1 graph, hypergraph, undirected graph, and graph in vector spaces. Real-world applications of these theories are spanned broadly in dimensionality reduction, subspace learning, manifold learning, clustering, classification, and feature selection. A selective group of experts contribute to different chapters of this book which provides a comprehensive perspective of this field.
Download or read book Machine Learning and Knowledge Discovery in Databases written by Hendrik Blockeel and published by Springer. This book was released on 2013-08-28 with total page 732 pages. Available in PDF, EPUB and Kindle. Book excerpt: This three-volume set LNAI 8188, 8189 and 8190 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2013, held in Prague, Czech Republic, in September 2013. The 111 revised research papers presented together with 5 invited talks were carefully reviewed and selected from 447 submissions. The papers are organized in topical sections on reinforcement learning; Markov decision processes; active learning and optimization; learning from sequences; time series and spatio-temporal data; data streams; graphs and networks; social network analysis; natural language processing and information extraction; ranking and recommender systems; matrix and tensor analysis; structured output prediction, multi-label and multi-task learning; transfer learning; bayesian learning; graphical models; nearest-neighbor methods; ensembles; statistical learning; semi-supervised learning; unsupervised learning; subgroup discovery, outlier detection and anomaly detection; privacy and security; evaluation; applications; and medical applications.
Download or read book Image Analysis written by Anders Heyden and published by Springer. This book was released on 2011-05-16 with total page 823 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 16th Scandinavian Conference on Image Analysis, SCIA 2011, held in Ystad, Sweden, in May 2011. The 74 revised full papers presented were carefully reviewed and selected from 140 submissions. The papers are organized in topical sections on multiple view geometry; segmentation; image analysis; categorization and classification; structure from motion and SLAM; medical and biomedical applications; 3D shape; medical imaging.
Download or read book Advances and applications of artificial intelligence in geoscience and remote sensing written by Peng Zhenming and published by Frontiers Media SA. This book was released on 2023-08-30 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Computer Vision ECCV 2016 written by Bastian Leibe and published by Springer. This book was released on 2016-09-16 with total page 910 pages. Available in PDF, EPUB and Kindle. Book excerpt: The eight-volume set comprising LNCS volumes 9905-9912 constitutes the refereed proceedings of the 14th European Conference on Computer Vision, ECCV 2016, held in Amsterdam, The Netherlands, in October 2016. The 415 revised papers presented were carefully reviewed and selected from 1480 submissions. The papers cover all aspects of computer vision and pattern recognition such as 3D computer vision; computational photography, sensing and display; face and gesture; low-level vision and image processing; motion and tracking; optimization methods; physics-based vision, photometry and shape-from-X; recognition: detection, categorization, indexing, matching; segmentation, grouping and shape representation; statistical methods and learning; video: events, activities and surveillance; applications. They are organized in topical sections on detection, recognition and retrieval; scene understanding; optimization; image and video processing; learning; action activity and tracking; 3D; and 9 poster sessions.
Download or read book Scale Space and Variational Methods in Computer Vision written by Luca Calatroni and published by Springer Nature. This book was released on 2023-05-09 with total page 767 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 9th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2023, which took place in Santa Margherita di Pula, Italy, in May 2023. The 57 papers presented in this volume were carefully reviewed and selected from 72 submissions. They were organized in topical sections as follows: Inverse Problems in Imaging; Machine and Deep Learning in Imaging; Optimization for Imaging: Theory and Methods; Scale Space, PDEs, Flow, Motion and Registration.
Download or read book Handbook of Combinatorial Optimization written by Ding-Zhu Du and published by Springer Science & Business Media. This book was released on 2013-12-01 with total page 2410 pages. Available in PDF, EPUB and Kindle. Book excerpt: Combinatorial (or discrete) optimization is one of the most active fields in the interface of operations research, computer science, and applied math ematics. Combinatorial optimization problems arise in various applications, including communications network design, VLSI design, machine vision, air line crew scheduling, corporate planning, computer-aided design and man ufacturing, database query design, cellular telephone frequency assignment, constraint directed reasoning, and computational biology. Furthermore, combinatorial optimization problems occur in many diverse areas such as linear and integer programming, graph theory, artificial intelligence, and number theory. All these problems, when formulated mathematically as the minimization or maximization of a certain function defined on some domain, have a commonality of discreteness. Historically, combinatorial optimization starts with linear programming. Linear programming has an entire range of important applications including production planning and distribution, personnel assignment, finance, alloca tion of economic resources, circuit simulation, and control systems. Leonid Kantorovich and Tjalling Koopmans received the Nobel Prize (1975) for their work on the optimal allocation of resources. Two important discover ies, the ellipsoid method (1979) and interior point approaches (1984) both provide polynomial time algorithms for linear programming. These algo rithms have had a profound effect in combinatorial optimization. Many polynomial-time solvable combinatorial optimization problems are special cases of linear programming (e.g. matching and maximum flow). In addi tion, linear programming relaxations are often the basis for many approxi mation algorithms for solving NP-hard problems (e.g. dual heuristics).
Download or read book Advanced Hybrid Information Processing written by Guan Gui and published by Springer Nature. This book was released on 2019-11-28 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set LNICST 301 -302 constitutes the post-conference proceedings of the Third EAI International Conference on Advanced Hybrid Information Processing, ADHIP 2019, held in Nanjing, China, in September 2019. The 101 papers presented were selected from 237 submissions and focus on hybrid big data processing. Since information processing has acted as an important research domain in science and technology today, it is now to develop deeper and wider use of hybrid information processing, especially information processing for big data. There are more remaining issues waiting for solving, such as classification and systemization of big data, objective tracking and behavior understanding in big multimedia data, encoding and compression of big data.
