检索结果-内蒙古大学图书馆

International conference on Fuzzy theory and it's applications (iFUZZY)

作者： Keiko Kida Seiki Ubukata Akira Notsu Katsuhiro Honda Graduate School of Engineering Osaka Prefecture University Sakai Osaka Japan Graduate School of Humanities and Sustainable System Sciences Osaka Prefecture University Sakai Osaka Japan

ISBN: (数字)9781728108407

ISBN: (纸本)9781728108414

Fuzzy co-clustering schemes including Fuzzy Co-Clustering induced by Multinomial Mixture models (FCCMM) are promising approaches for analyzing object-item cooccur-renee information such as document-keyword frequencies and customer-product purchase history transactions. However, such cooccurrence datasets are generally maintained as very large matrices and cannot be dealt with conventional batch algorithms. In order to deal with such problems, online FCCMM (OFC-CMM) that sequentially loads a single object has been proposed. Conventional OFCCMM uses stochastic gradient descent (SGD) to update parameters. SGD generally has drawbacks that convergence is slow and it is susceptible to vibration state and a saddle point. Many improvements on SGD have been proposed such as Momentum SGD, Nesterov's accelerated gradient method, AdaGrad, and Adam. In this study, we introduce various gradient descent methods into OFCCMM and observe their characteristics and performance through numerical experiments.

关键词： Clustering algorithms Acceleration Convergence linear programming Gradient methods Mixture models Vibrations

来源：评论

学校读者我要写书评

暂无评论

Stochastic Bregman Parallel Direction Method of Multipliers for Distributed Optimization

Stochastic Bregman Parallel Direction Method of Multipliers ...

引用

IEEE Annual conference on Decision and Control

作者： Yue Yu Behcet Acikmese Department of Aeronautics and Astronautics University of Washington Seattle WA USA

ISBN: (数字)9781728113982

ISBN: (纸本)9781728113999

Bregman parallel direction method of multipliers (BPDMM) efficiently solves distributed optimization over a network, which arises in a wide spectrum of collaborative multi-agent learning applications. In this paper, we generalize BPDMM to stochastic BPDMM, where each iteration only solves local optimization on a randomly selected subset of nodes rather than all the nodes in the network. Such generalization reduce the need for computational resources and allows applications to larger scale networks. We establish both the global convergence and the O(1/T) iteration complexity of stochastic BPDMM. We demonstrate our results via numerical examples.

关键词： Optimization Convergence Mirrors Lyapunov methods Symmetric matrices Complexity theory linear matrix inequalities

来源：评论

学校读者我要写书评

暂无评论

A Competitive Error in Variables Approach and Algorithms for Finding Positive Definite Solutions of linear Systems of Matrix Equations 1

引用

4th International conference on numerical Analysis and Optimization (NAO) - theory, methods, applications and Technology Transfer (NAOIV)

作者： Bagherpour, Negin Mandavi-Amiri, Nezam Univ Manchester Dept Math Manchester Lancs England Sharif Univ Technol Fac Math Sci Tehran Iran

ISBN: (数字)9783319900261

ISBN: (纸本)9783319900261;9783319900254

Here, we refine our recent proposed method for computing a positive definite solution to an overdetermined linear system of equations with multiple right-hand sides. This problem is important in several process control contexts including quadratic models for optimal control. The coefficient and the right-hand side matrices are, respectively, named data and target matrices. In several existing approaches, the data matrix is unrealistically assumed to be error free. We have recently presented an algorithm for solving such a problem considering error in measured data and target matrices. We defined a new error in variables (EIV) error function considering error for the variables, the necessary and sufficient optimality conditions and outlined an algorithm to directly compute a solution minimizing the defined error. Moreover, the algorithm was specialized for a special case when the data and target matrices are rank deficient. Here, after giving a detailed review of the proposed algorithms, we rewrite the algorithms by use of the Householder tridiagonalization instead of spectral decomposition. We then show that in case of full rank data and target matrices, the Householder tridiagonalization is more efficient than the previously considered spectral decomposition. A comparison of our proposed approach and two existing methods are provided. The numerical test results and the associated Dolan-More performance profiles show the new approach to be more efficient than the two methods and have comparatively smaller standard deviation of error entries and smaller effective rank as features being sought for control problems.

关键词： linear systems Positive definite solution Error in variables model Householder tridiagonalization

来源：评论

学校读者我要写书评

暂无评论

Influence of elements of coupling stiffness sub-matrix on nonlinear stability FGM-FML thin-walled columns with open cross-section 11th

Influence of elements of coupling stiffness sub-matrix on no...

引用

11th International conference on Shell Structures: theory and applications, SSTA 2017

作者： Kolakowski, Z. Mania, R.J. Teter, A. Lodz University of Technology Lodz Poland Lublin University of Technology Lublin Poland

ISBN: (纸本)9781138050457

The study of coupled instabilities of thin-walled columns with open cross-sections, made of Functionally Graded Materials (FGMs) and Fibre Metal Laminates (FMLs) is presented. The FGM layers are a thermal barrier whereas the FML composite laminate provides rigidity and strength. The non-linear problem of buckling was solved by the analytical-numerical method (ANM) based on Koiter’s theory using the classical laminate theory. Interaction of the global buckling modes with different local buckling modes was discussed. A plate model of thin-walled structures was adopted. Each column was made of a FML sublayer, a single AL-TiC-type FGM layer and a TiC ceramic layer. The layup configuration of the FML-FGM composite is nonsymmetric, so the coupling matrix B is non-trivial. The influence of particular matrix B elements on stability and load-carrying capacity of open cross-section columns was analyzed. © 2018 Taylor & Francis Group, London.

关键词： numerical methods

来源：评论

学校读者我要写书评

暂无评论

Applied linear algebra 2

引用

丛书名： Undergraduate texts in mathematics

2018年

作者： Peter J. Olver Chehrzad Shakiban

ISBN: (数字)9783319910413

ISBN: (纸本)9783319910406

This textbook develops the essential tools of linear algebra, with the goal of imparting technique alongside contextual understanding. applications go hand-in-hand with theory, each reinforcing and explaining the other. This approach encourages students to develop not only the technical proficiency needed to go on to further study, but an appreciation for when, why, and how the tools of linear algebra can be used across modern applied *** an extensive treatment of essential topics such as Gaussian elimination, inner products and norms, and eigenvalues and singular values, this text can be used for an in-depth first course, or an application-driven second course in linear algebra. In this second edition, applications have been updated and expanded to include numerical methods, dynamical systems, data analysis, and signal processing, while the pedagogical flow of the core material has been improved. Throughout, the text emphasizes the conceptual connections between each application and the underlying linear algebraic techniques, thereby enabling students not only to learn how to apply the mathematical tools in routine contexts, but also to understand what is required to adapt to unusual or emerging *** previous knowledge of linear algebra is needed to approach this text, with single-variable calculus as the only formal prerequisite. However, the reader will need to draw upon some mathematical maturity to engage in the increasing abstraction inherent to the subject. Once equipped with the main tools and concepts from this book, students will be prepared for further study in differential equations, numerical analysis, data science and statistics, and a broad range of applications. The first author’s text, Introduction to Partial Differential Equations, is an ideal companion volume, forming a natural extension of the linear mathematical methods developed here.

关键词： algebras linear Mathematics

来源：评论

学校读者我要写书评

暂无评论

Efficient data-driven geologic feature characterization from pre-stack seismic measurements using randomized machine learning algorithm

引用

GEOPHYSICAL JOURNAL INTERNATIONAL 2018年第3期215卷 1900-1913页

作者： Lin, Youzuo Wang, Shusen Thiagarajan, Jayaraman Guthrie, George Coblentz, David Los Alamos Natl Lab Earth & Environm Div Los Alamos NM 87545 USA Univ Calif Berkeley Dept Stat Berkeley CA 94720 USA Lawrence Livermore Natl Lab Ctr Appl Sci Comp Livermore CA 94550 USA

Conventional seismic techniques for detecting the subsurface geologic features are challenged by limited data coverage, computational inefficiency and subjective human factors. We developed a novel data-driven geological feature characterization approach based on pre-stack seismicmeasurements. Our characterization method employs an efficient and accuratemachine learning method to extract useful subsurface geologic features automatically. Specifically, we use kernel ridge regression to account for the nonlinear relationship between seismic data and geological features. We further employ kernel tricks to avoid the explicit nonlinear mapping and infinite dimension of feature space. However, the conventional kernel ridge regression can be computationally prohibitive because of the large volume of seismic measurements. We employ a data reduction technique in combination with the conventional kernel ridge regression method to improve the computational efficiency and reduce memory usage. In particular, we utilize a randomized numerical linear algebra technique, named Nystrom method, to effectively reduce the dimensionality of the feature space without compromising the information content required for accurate characterization. We provide thorough computational cost analysis to show the efficiency of our new geological feature characterization methods. We validate the performance of our method in characterizing geologic fault zones because faults play an important role in various subsurface applications. Our numerical examples demonstrate that our new characterization method significantly improves the computational efficiency while maintaining comparable accuracy. Interestingly, we show that our method yields a speedup ratio on the order of similar to 10(2) to similar to 10(3) in a multicore computational environment.

关键词： Inverse theory numerical Solutions Computational Seismology Neural Networks

来源：评论

学校读者我要写书评

暂无评论

Information Bottleneck Problem Revisited

Information Bottleneck Problem Revisited

引用

Annual Allerton conference on Communication, Control, and Computing

作者： Farhang Bayat Shuangqing Wei School of EECS Louisiana State University Baton Rouge LA USA

In this paper, we revisit the information bottleneck problem whose formulation and solution are of great importance in both information theory and statistical learning applications. We go into details as to why the problem was first introduced and how the algorithm proposed using Lagrangian method to solve such problems fell short of an exact solution. We then revisit the limitations of such Lagrangian methods, and propose to adopt a more systematic method, namely, Alternate Direction Method of Multipliers (ADMM) to develop a more efficient ADMM algorithm with randomized permutation orders to solve such problems. More importantly, we mathematically demonstrate how our suggested method outperforms the original Information Bottleneck (IB) method. At the end, we provide numerical results to demonstrate the notable advantages our algorithm attains as compared with the well-known IB approach in terms of both attained objective function values and the resulting constraints. We further inspect the concepts of accuracy and convergence and the trade-off between them in our method.

关键词： Optimization Mutual information Convergence Systematics linear programming Markov processes Iterative methods

来源：评论

学校读者我要写书评

暂无评论

Optimally Sample-Efficient Phase Retrieval with Deep Generative Models

Optimally Sample-Efficient Phase Retrieval with Deep Generat...

引用

International conference on Sampling theory and applications (SampTA)

作者： Paul Hand Oscar Leong Vladislav Voroninski Department of Mathematics & Computer Science Northeastern University Department of Computational & Applied Mathematics Rice University Helm.ai

ISBN: (数字)9781728137414

ISBN: (纸本)9781728137421

We consider the phase retrieval problem, which asks to recover a structured n-dimensional signal from m quadratic measurements. In many imaging contexts, it is beneficial to enforce a sparsity prior on the signal to reduce the number of measurements necessary for recovery. However, the best known methodologies for sparse phase retrieval have a sub-optimal quadratic dependency on the sparsity level of the signal at hand. In this work, we instead model signals as living in the range of a deep generative neural network G : ℝ k → ℝ n . We show that under the model of a d-layer feed forward neural network with Gaussian weights, m = O(kd 2 log n) generic measurements suffice for the ℓ 2 empirical risk minimization problem to have favorable geometry. In particular, we exhibit a descent direction for all points outside of two arbitrarily small neighborhoods of the true k-dimensional latent code and a negative reflection of it. Our proof is based on showing the sufficiency of two deterministic conditions on the generator and measurement matrices, which are satisfied with high probability under random Gaussian ensembles. We corroborate these results with numerical experiments showing that enforcing a generative prior via empirical risk minimization outperforms sparse phase retrieval methods.

关键词： linear programming Phase measurement Weight measurement Risk management Geometry Generators Neurons

来源：评论

学校读者我要写书评

暂无评论

A Non-linear Arithmetic Procedure for Control-Command Software Verification 24th

A Non-linear Arithmetic Procedure for Control-Command Softwa...

引用

24th International conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS) Held as Part of the 21st European Joint conferences on theory and Practice of Software (ETAPS)

作者： Roux, Pierre Iguernlala, Mohamed Conchon, Sylvain Off Natl Etud & Rech Aerosp DTIS F-31055 Toulouse France OCamlPro SAS F-91190 Gif Sur Yvette France Univ Paris Sud LRI F-91405 Orsay France INRIA Saclay Ile de France F-91893 Orsay France

ISBN: (纸本)9783319899633;9783319899633

State-of-the-art (semi-)decision procedures for non-linear real arithmetic address polynomial inequalities by mean of symbolic methods, such as quantifier elimination, or numerical approaches such as interval arithmetic. Although (some of) these methods offer nice completeness properties, their high complexity remains a limit, despite the impressive efficiency of modern implementations. This appears to be an obstacle to the use of SMT solvers when verifying, for instance, functional properties of control-command programs. Using off-the-shelf convex optimization solvers is known to constitute an appealing alternative. However, these solvers only deliver approximate solutions, which means they do not readily provide the soundness expected for applications such as software verification. We thus investigate a-posteriori validation methods and their integration in the SMT framework. Although our early prototype, implemented in the Alt-Ergo SMT solver, often does not prove competitive with state of the art solvers, it already gives some interesting results, particularly on control-command programs.

关键词： SMT Non-linear real arithmetic Polynomial inequalities Convex optimization

来源：评论

学校读者我要写书评

暂无评论

Gauss-Seidel progressive iterative approximation (GS-PIA) for Loop surface interpolation 26

Gauss-Seidel progressive iterative approximation (GS-PIA) fo...

引用

26th Pacific conference on Computer Graphics and applications, Pacific Graphics 2018

作者： Wang, Zhihao Li, Yajuan Ma, Weiyin Deng, Chongyang School of Sciences Hangzhou Dianzhi University Hangzhou China Department of Mechanical Engineering City University of Hong Kong Hong Kong

ISBN: (纸本)9783038680734

We propose a Gauss-Seidel progressive iterative approximation (GS-PIA) method for Loop subdivision surface interpolation by combining classical Gauss-Seidel iterative method for linear system and progressive iterative approximation (PIA) for data interpolation. We prove that GS-PIA is convergent by applying matrix theory. GS-PIA algorithm retains the good features of the classical PIA method, such as the resemblance with the given mesh and the advantages of both a local method and a global method. Compared with some existed interpolation methods of subdivision surfaces, GS-PIA algorithm has advantages in three aspects. First, it has a faster convergence rate compared with the PIA and WPIA algorithms. Second, compared with WPIA algorithm, GS-PIA algorithm need not to choose weights. Third, GS-PIA need not to modify the mesh topology compared with other methods with fairness measures. numerical examples for Loop subdivision surfaces interpolation illustrated in this paper show the efficiency and effectiveness of GS-PIA algorithm. © 2018 The Author(s).

关键词： linear systems

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：