检索结果-内蒙古大学图书馆

28th ACM International Conference on Information and Knowledge Management (CIKM)

作者： Wang, Zigeng Mamun, Abdullah-Al Cai, Xingyu Ravishanker, Nalini Rajasekaran, Sanguthevar Univ Connecticut Dept Comp Sci & Engr Storrs CT 06269 USA Univ Connecticut Dept Stat Storrs CT 06269 USA Google LLC Mountain View CA USA

ISBN: (纸本)9781450369763

Higher order spectra (HOS) are a powerful tool in nonlinear time series analysis and they have been extensively used as feature representations in data mining, communications and cosmology domains. However, HOS estimation suffers from high computational cost and memory consumption. Any algorithm for computing the kth order spectra on a dataset of size n needs Omega(n(k-1)) time since the output size will be Omega(n(k-1)) as well, which makes the direct HOS analysis difficult for long time series, and further prohibits its direct deployment to resource-limited and time-sensitive applications. Existing algorithms for computing HOS are either inefficient or have been implemented on obsolete architectures. Thus it is essential to develop efficient generic algorithms for HOS estimations. In this paper, we present a package of generic sequential and parallel algorithms for computationally and memory efficient HOS estimations which can be employed on any parallel machine or platform. Our proposed algorithms largely reduce the HOS' computational cost and memory usage in spectrum multiplication and smoothing steps through carefully designed prefix sum operations. Moreover, we employ a matrix partitioning technique and design algorithms with optimal memory usage and present the parallel approaches on the PRAM and the mesh models. Furthermore, we implement our algorithms for both bispectrum and trispectrum estimations. We conduct extensive experiments and cross-compare the proposed algorithms' performance. Results show that our algorithms achieve state-of-the-art computational and memory efficiency, and our parallel algorithms achieve close to linear speedups.

关键词： higher order spectra sequential algorithms parallel algorithms memory efficient algorithms linear speedups

来源：评论

学校读者我要写书评

暂无评论

sequential Randomized algorithms for Convex Optimization in the Presence of Uncertainty

引用

IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2016年第9期61卷 2565-2571页

作者： Chamanbaz, Mohammadreza Dabbene, Fabrizio Tempo, Roberto Venkataramanan, Venkatakrishnan Wang, Qing-Guo Data Storage Inst Singapore 138632 Singapore Natl Univ Singapore Dept Elect & Comp Engn Singapore 119077 Singapore Politecn Torino CNR IEIIT I-10129 Turin Italy

In this technical note, we propose new sequential randomized algorithms for convex optimization problems in the presence of uncertainty. A rigorous analysis of the theoretical properties of the solutions obtained by these algorithms, for full constraint satisfaction and partial constraint satisfaction, respectively, is given. The proposed methods allow to enlarge the applicability of the existing randomized methods to real-world applications involving a large number of design variables. Since the proposed approach does not provide a priori bounds on the sample complexity, extensive numerical simulations, dealing with an application to hard-disk drive servo design, are provided. These simulations testify the goodness of the proposed solution.

关键词： Convex optimization hard-disk servo design randomized algorithms sequential algorithms

来源：评论

学校读者我要写书评

暂无评论

sequential algorithms for Unbounded Nondeterminism

引用

ELECTRONIC NOTES IN THEORETICAL COMPUTER SCIENCE 2015年 319卷 271-287页

作者： Laird, J. Univ Bath Dept Comp Sci Bath BA2 7AY Avon England

We give extensional and intensional characterizations of higher-order functional programs with unbounded nondeterminism: as stable and monotone functions between the biorders of states of ordered concrete data structures, and as sequential algorithms (states of an exponential ocds) which compute them. Our fundamental result establishes that these representations are equivalent, by showing how to construct a unique sequential algorithm which computes a given stable and monotone function. We illustrate by defining a denotational semantics for a functional language with countable nondeterminism ("fair PCF"), with an interpretation of fixpoints which allows this to be proved to be computationally adequate. We observe that our model contains functions which cannot be computed in fair PCF, by identifying a further property of the definable elements, and so show that it is not fully abstract.

关键词： sequential algorithms Nondeterminism Fairness Biorders

来源：评论

学校读者我要写书评

暂无评论

sequential algorithms for structural design optimization under tolerance conditions

引用

ENGINEERING OPTIMIZATION 2014年第9期46卷 1183-1199页

作者： Chen, Jianqiao Tang, Yuanfu Huazhong Univ Sci & Technol Dept Mech Hubei Key Lab Engn Struct Anal & Safety Assessmen Wuhan 430074 Peoples R China

A deterministic optimization usually ignores the effects of uncertainties in design variables or design parameters on the constraints. In practical applications, it is required that the optimum solution can endure some tolerance so that the constraints are still satisfied when the solution undergoes variations within the tolerance range. An optimization problem under tolerance conditions is formulated in this article. It is a kind of robust design and a special case of a generalized semi-infinite programming (GSIP) problem. To overcome the deficiency of directly solving the double loop optimization, two sequential algorithms are then proposed for obtaining the solution, i.e. the double loop optimization is solved by a sequence of cycles. In each cycle a deterministic optimization and a worst case analysis are performed in succession. In sequential algorithm 1 (SA1), a shifting factor is introduced to adjust the feasible region in the next cycle, while in sequential algorithm 2 (SA2), the shifting factor is replaced by a shifting vector. Several examples are presented to demonstrate the efficiency of the proposed methods. An optimal design result based on the presented method can endure certain variation of design variables without violating the constraints. For GSIP, it is shown that SA1 can obtain a solution with equivalent accuracy and efficiency to a local reduction method (LRM). Nevertheless, the LRM is not applicable to the tolerance design problem studied in this article.

关键词： tolerance conditions robust design structural design optimization sequential algorithms GSIP

来源：评论

学校读者我要写书评

暂无评论

hermiter: R package for sequential nonparametric estimation

引用

COMPUTATIONAL STATISTICS 2024年第3期39卷 1127-1163页

作者： Stephanou, Michael Varughese, Melvin Rand Merchant Bank Johannesburg South Africa Univ Cape Town Cape Town South Africa Univ Western Australia Perth Australia

This article introduces the R package hermiter which facilitates estimation of univariate and bivariate probability density functions and cumulative distribution functions along with full quantile functions (univariate) and nonparametric correlation coefficients (bivariate) using Hermite series based estimators. The algorithms implemented in the hermiter package are particularly useful in the sequential setting (both stationary and non-stationary) and one-pass batch estimation setting for large data sets. In addition, the Hermite series based estimators are approximately mergeable allowing parallel and distributed estimation.

关键词： Fast Kendall Tau Fast quantiles Fast Spearman Rho Hermite series estimators Online algorithms sequential algorithms

来源：评论

学校读者我要写书评

暂无评论

EXTENSIONAL AND INTENSIONAL MODELS FOR BOUNDED AND UNBOUNDED NONDETERMINISM

引用

LOGICAL METHODS IN COMPUTER SCIENCE 2021年第4期17卷 11:1-11:37页

作者： Laird, J. Univ Bath Dept Comp Sci Bath Avon England

We give extensional and intensional characterizations of functional programs with nondeterminism: as structure preserving functions between biorders, and as nondeterministic sequential algorithms on ordered concrete data structures which compute them. A fundamental result establishes that these extensional and intensional representations are equivalent, by showing how to construct the unique sequential algorithm which computes a given monotone and stable function, and describing the conditions on sequential algorithms which correspond to continuity with respect to each order. We illustrate by defining may-testing and must-testing denotational semantics for sequential functional languages with bounded and unbounded choice operators. We prove that these are computationally adequate, despite the non-continuity of the must-testing semantics of unbounded nondeterminism. In the bounded case, we prove that our continuous models are fully abstract with respect to may-testing and must-testing by identifying a simple universal type, which may also form the basis for models of the untyped lambda-calculus. In the unbounded case we observe that our model contains computable functions which are not denoted by terms, by identifying a further \weak continuity" property of the definable elements, and use this to establish that it is not fully abstract.

关键词： Nondeterminism Denotational Semantics Biorders sequential algorithms

来源：评论

学校读者我要写书评

暂无评论

Asymptotic optimality of degree-greedy discovering of independent sets in Configuration Model graphs

引用

STOCHASTIC PROCESSES AND THEIR APPLICATIONS 2021年 131卷 122-150页

作者： Jonckheere, Matthieu Saenz, Manuel Univ Buenos Aires Inst Calculo CONICET Buenos Aires DF Argentina Univ Buenos Aires Math Dept FCEyN Buenos Aires DF Argentina

Finding independent sets of maximum size in fixed graphs is well known to be an NP-hard task. Using scaling limits, we characterise the asymptotics of sequential degree-greedy explorations and provide sufficient conditions for this algorithm to find an independent set of asymptotically optimal size in large sparse random graphs with given degree sequences. In the special case of sparse Erdos-Renyi graphs, our results allow to give a simple proof of the so-called e-phenomenon identified by Karp and Sipser for matchings and to give an alternative characterisation of the asymptotic independence number. (C) 2020 Elsevier B.V. All rights reserved.

关键词： Random graphs sequential algorithms Maximum independent sets Hydrodynamic limits

来源：评论

学校读者我要写书评

暂无评论

Optimizing regular computations based on neural networks and Graph Traversal 14

Optimizing regular computations based on neural networks and...

引用

14th International Symposium on Intelligent Systems

作者： Mohammed, O. T. Heidari, M. S. Paznikov, A. A. St Petersburg Electrotech Univ LETI Dept Comp Sci Knowledge & Discovery Ul Prof Popova 5 St Petersburg 197376 Russia

In recent days we can see that multicore computers have the ability to easily manipulate digit numbers however as numbers get bigger the computation becomes more complex, the reason is that the size of both CPU registers and buses is limited. As a result, the arithmetic operations such as addition, subtraction, multiplication, and division for CPU become more complex to perform. For solving the problem of how to do computation on big digit numbers, a number of algorithms have been developed. However, the existing algorithms are noticeably slow because they operate on bits individually and are designed to run over single-core computers only. In this paper, an AI model is presented that performs a computation on tokens of 8 -digit numbers to assist boost the CPU computation performance.. (C) 2021 The Authors. Published by Elsevier B.V.

关键词： Node iteration algorithms sequential algorithms Parallel algorithms Neural networks

来源：评论

学校读者我要写书评

暂无评论

sequential community mode estimation

引用

PERFORMANCE EVALUATION 2021年 152卷

作者： Jain, Shubham Anand Goenka, Shreyas Bapna, Divyam Karamchandani, Nikhil Nair, Jayakrishnan Indian Inst Technol Dept Elect Engn Mumbai Maharashtra India

We consider a population, partitioned into a set of communities, and study the problem of identifying the largest community within the population via sequential, random sampling of individuals. There are multiple sampling domains, referred to as boxes, which also partition the population. Each box may consist of individuals of different communities, and each community may in turn be spread across multiple boxes. The learning agent can, at any time, sample (with replacement) a random individual from any chosen box;when this is done, the agent learns the community the sampled individual belongs to, and also whether or not this individual has been sampled before. The goal of the agent is to minimize the probability of mis-identifying the largest community in a fixed budget setting, by optimizing both the sampling strategy as well as the decision rule. We propose and analyse novel algorithms for this problem, and also establish information theoretic lower bounds on the probability of error under any algorithm. In several cases of interest, the exponential decay rates of the probability of error under our algorithms are shown to be optimal up to constant factors. The proposed algorithms are further validated via simulations on real-world datasets. (C) 2021 Elsevier B.V. All rights reserved.

关键词： Mode estimation Limited precision sampling sequential algorithms Fixed budget Multi-armed bandits

来源：评论

学校读者我要写书评

暂无评论

Optimizing regular computations based on neural networks and Graph Traversal

引用

Procedia Computer Science 2021年 186卷 337-343页

作者： O.T. Mohammed M.S. Heidari A.A. Paznikov Department of computer science knowledge and discovery Saint Petersburg Electrotechnical University “LETI” ul. Professora Popova 5 St. Petersburg 197376 Russia

In recent days we can see that multicore computers have the ability to easily manipulate digit numbers however as numbers get bigger the computation becomes more complex, the reason is that the size of both CPU registers and buses is limited. As a result, the arithmetic operations such as addition, subtraction, multiplication, and division for CPU become more complex to perform. For solving the problem of how to do computation on big digit numbers, a number of algorithms have been developed. However, the existing algorithms are noticeably slow because they operate on bits individually and are designed to run over single-core computers only. In this paper, an AI model is presented that performs a computation on tokens of 8-digit numbers to assist boost the CPU computation performance.

关键词： Node iteration algorithms sequential algorithms Parallel algorithms Neural networks

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：