標題: Titlebook: Large-Scale and Distributed Optimization; Pontus Giselsson,Anders Rantzer Book 2018 Springer Nature Switzerland AG 2018 Large-Scale Optimi [打印本頁] 作者: 復雜 時間: 2025-3-21 20:02
書目名稱Large-Scale and Distributed Optimization影響因子(影響力)
書目名稱Large-Scale and Distributed Optimization影響因子(影響力)學科排名
書目名稱Large-Scale and Distributed Optimization網(wǎng)絡(luò)公開度
書目名稱Large-Scale and Distributed Optimization網(wǎng)絡(luò)公開度學科排名
書目名稱Large-Scale and Distributed Optimization被引頻次
書目名稱Large-Scale and Distributed Optimization被引頻次學科排名
書目名稱Large-Scale and Distributed Optimization年度引用
書目名稱Large-Scale and Distributed Optimization年度引用學科排名
書目名稱Large-Scale and Distributed Optimization讀者反饋
書目名稱Large-Scale and Distributed Optimization讀者反饋學科排名
作者: expunge 時間: 2025-3-21 20:39
Large-Scale and Distributed Optimization978-3-319-97478-1Series ISSN 0075-8434 Series E-ISSN 1617-9692 作者: 女歌星 時間: 2025-3-22 04:28
Pontus Giselsson,Anders RantzerContributes to current and upcoming research on large-scale and distributed optimization.Covers the increasingly important tools and methods for large-scale optimization.Offers a valuable source of in作者: VAN 時間: 2025-3-22 06:08
Lecture Notes in Mathematicshttp://image.papertrans.cn/l/image/581426.jpg作者: apiary 時間: 2025-3-22 12:07
https://doi.org/10.1007/978-3-319-97478-1Large-Scale Optimization; Distributed Optimization; Operator Splitting Methods; Machine Learning; Convex作者: Priapism 時間: 2025-3-22 14:46 作者: AND 時間: 2025-3-22 18:31
Frank-Wolfe Style Algorithms for Large Scale Optimization,rithm using stochastic gradients, approximate subproblem solutions, and sketched decision variables in order to scale to enormous problems while preserving (up to constants) the optimal convergence rate ..作者: achlorhydria 時間: 2025-3-22 23:59 作者: liposuction 時間: 2025-3-23 01:57 作者: 谷物 時間: 2025-3-23 05:34
Decomposition Methods for Large-Scale Semidefinite Programs with Chordal Aggregate Sparsity and ParIn this chapter, we review two decomposition frameworks for large-scale SDPs characterized by either chordal aggregate sparsity or partial orthogonality. Chordal aggregate sparsity allows one to decompose the positive semidefinite matrix variable in the SDP, while partial orthogonality enables the d作者: 跑過 時間: 2025-3-23 11:50 作者: 真 時間: 2025-3-23 16:32
Primal-Dual Proximal Algorithms for Structured Convex Optimization: A Unifying Framework, and two nonsmooth proximable functions, one of which is composed with a linear mapping. The framework is based on the recently proposed asymmetric forward-backward-adjoint three-term splitting (AFBA); depending on the value of two parameters, (extensions of) known algorithms as well as many new pri作者: 無瑕疵 時間: 2025-3-23 19:49 作者: 類人猿 時間: 2025-3-24 00:19 作者: 馬籠頭 時間: 2025-3-24 03:21
Mirror Descent and Convex Optimization Problems with Non-smooth Inequality Constraints,hods to solve such problems in different situations: smooth or non-smooth objective function; convex or strongly convex objective and constraint; deterministic or randomized information about the objective and constraint. Described methods are based on Mirror Descent algorithm and switching subgradi作者: Interdict 時間: 2025-3-24 08:20
Frank-Wolfe Style Algorithms for Large Scale Optimization,rithm using stochastic gradients, approximate subproblem solutions, and sketched decision variables in order to scale to enormous problems while preserving (up to constants) the optimal convergence rate ..作者: Chemotherapy 時間: 2025-3-24 13:27 作者: 無法取消 時間: 2025-3-24 17:46
Communication-Efficient Distributed Optimization of Self-concordant Empirical Loss,ization in machine learning. We assume that each machine in the distributed computing system has access to a local empirical loss function, constructed with i.i.d. data sampled from a common distribution. We propose a communication-efficient distributed algorithm to minimize the overall empirical lo作者: COKE 時間: 2025-3-24 19:47 作者: 主講人 時間: 2025-3-24 23:29
Convergence of an Inexact Majorization-Minimization Method for Solving a Class of Composite Optimizy constructed . of the objective function. We describe a variety of classes of functions for which such a construction is possible. We introduce an inexact variant of the method, in which only approximate minimization of the consistent majorizer is performed at each iteration. Both the exact and the作者: 制定法律 時間: 2025-3-25 04:13 作者: carotid-bruit 時間: 2025-3-25 09:04
uctured instruments serving as ‘readable technologies‘. " Scientific knowledge should thus be understood as an extension of "unassisted" perception. A perceptual fact has an outer horizon "which separates it from the ground on which it appears," and an inner horizon "composed of a multiplicity of po作者: browbeat 時間: 2025-3-25 13:14
Yang Zheng,Giovanni Fantuzzi,Antonis Papachristodoulou作者: Respond 時間: 2025-3-25 16:39
Anastasia Bayandina,Pavel Dvurechensky,Alexander Gasnikov,Fedor Stonyakin,Alexander Titov作者: ENACT 時間: 2025-3-25 21:19
Robert Baier,Philipp Braun,Lars Grüne,Christopher M. Kellett作者: Vulvodynia 時間: 2025-3-26 03:11 作者: Evacuate 時間: 2025-3-26 05:59 作者: endoscopy 時間: 2025-3-26 08:36 作者: Promotion 時間: 2025-3-26 14:49 作者: 山崩 時間: 2025-3-26 17:44 作者: 一條卷發(fā) 時間: 2025-3-27 00:18 作者: ticlopidine 時間: 2025-3-27 03:06
t by a "many-to-one or one-to- many application between contextually defined perceptual objects within contexts that are mutually incompatible but complementary. " This should not, however, be 978-90-481-5926-0978-94-017-1767-0Series ISSN 0068-0346 Series E-ISSN 2214-7942 作者: 表皮 時間: 2025-3-27 08:34 作者: Allure 時間: 2025-3-27 11:35
Decentralized Consensus Optimization and Resource Allocation,r solving the decentralized consensus optimization problem and, based on the “mirror relationship”, we then develop some algorithms for solving the decentralized resource allocation problem. We also provide some numerical experiments to demonstrate the efficacy of the algorithms and validate the methodology of using the “mirror relation”.作者: 要素 時間: 2025-3-27 14:09
0075-8434 for large-scale optimization.Offers a valuable source of inThis book presents tools and methods for large-scale and distributed optimization. Since many methods in "Big Data" fields rely on solving large-scale optimization problems, often in distributed fashion, this topic has over the last decade 作者: 場所 時間: 2025-3-27 20:15
Exploiting Chordality in Optimization Algorithms for Model Predictive Control,point method for solving the problem. The chordal structure can stem both from the sequential nature of the problem as well as from distributed formulations of the problem related to scenario trees or other formulations. The framework enables efficient parallel computations.作者: 收到 時間: 2025-3-28 00:35
Smoothing Alternating Direction Methods for Fully Nonsmooth Constrained Convex Optimization,to update all the algorithmic parameters automatically with clear impact on the convergence performance. We also provide a representative numerical example showing the advantages of our methods over the classical alternating direction methods using a well-known feasibility problem.作者: Emmenagogue 時間: 2025-3-28 04:37 作者: 熱心 時間: 2025-3-28 08:36
Mirror Descent and Convex Optimization Problems with Non-smooth Inequality Constraints, also construct Mirror Descent for problems with objective function, which is not Lipschitz, e.g., is a quadratic function. Besides that, we address the question of recovering the dual solution in the considered problem.作者: dissolution 時間: 2025-3-28 10:54 作者: Foam-Cells 時間: 2025-3-28 17:34
Primal-Dual Proximal Algorithms for Structured Convex Optimization: A Unifying Framework,mal-dual schemes are obtained. This allows for a unified analysis that, among other things, establishes linear convergence under four different regularity assumptions for the cost functions. Most notably, linear convergence is established for the class of problems with piecewise linear-quadratic cost functions.作者: Pastry 時間: 2025-3-28 21:13
Book 2018 optimization problems, often in distributed fashion, this topic has over the last decade emerged to become very important. As well as specific coverage of this active research field, the book serves as a powerful source of information for practitioners as well as theoreticians..Large-Scale and Dist作者: antiandrogen 時間: 2025-3-29 01:00
Teacher Guidance in Mathematical Problem-Solving Lessons: Insights from Two Professional Development Programsuires understanding students’ work in progress and giving them necessary help without constraining their thinking. In this article, we share insights from two professional development programs on how teachers guided students’ problem solving and how they reflected on these instances. One of the prog作者: geometrician 時間: 2025-3-29 06:49
The Empirical Journey Begins: Meanings of Transnational Strategic Alliances,tional level transnational strategic alliances of institutions of higher education in the sample. Their influence was evident in their policies, advice and funding for these types of partnerships at the higher education institutions in the sample. This would also explain why the majority of the inst作者: Fecundity 時間: 2025-3-29 09:18
2192-4791 and problems with solutions.Discusses more advanced topics a.This book, the first in a two-volume set, provides an introduction to the fundamentals of (mainly) non-relativistic quantum mechanics. This first volume chiefly focuses on the essential principles, while applications and extensions of the 作者: 黃瓜 時間: 2025-3-29 12:25
Faustino Gomezenses, the majority of people are not receiving proper medical care. AI-enabled remote monitoring systems improve patient-centred access to quality services and guidance for proactive self-management. In this chapter, we review various AI and machine learning techniques applied for remote pregnancy monitoring and risk prediction.作者: PLE 時間: 2025-3-29 19:18 作者: Forage飼料 時間: 2025-3-29 23:10 作者: PANG 時間: 2025-3-30 00:43 作者: infinite 時間: 2025-3-30 04:56
Pulp Response to Clinical Procedures and Dental Materials,orative dentistry, using minimally invasive operative techniques associated with applying dental materials that present scientifically proven properties to be safely employed in specific clinical situations must be routine for clinicians. This professional and responsible attitude will undoubtedly r作者: spinal-stenosis 時間: 2025-3-30 10:55
Hans Klingelh?fferology. Thompson’s unique and insightful approach to addressing the risks and questions of public acceptability associated with novel technology stands as a model for anyone interested in technological innovatio978-90-481-7446-1978-1-4020-5791-5Series ISSN 1570-3010 Series E-ISSN 2215-1737 作者: LAY 時間: 2025-3-30 14:58 作者: SKIFF 時間: 2025-3-30 18:27 作者: ARM 時間: 2025-3-31 00:05
,Was-W?re-Wenn-Analysen — Die praxisnahe Organisation von Tabellen,Dieses Kapitel
