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检索条件"主题词=distributed computation"

共 513 条记录，以下是401-410 订阅

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A Study of distributed MOEA/D Based on Spark Framework 19

A Study of Distributed MOEA/D Based on Spark Framework

引用

19th IEEE International Conference on High Performance Computing and Communications (HPCC) / 15th IEEE International Conference on Smart City (SmartCity) / 3rd IEEE International Conference on Data Science and Systems (DSS)

作者： Zhang, Defu Ma, Yingdong Chen, Jinxiu Xiamen Univ Dept Comp Sci Xiamen Peoples R China

ISBN: (纸本)9781538625880

We carry out a careful study of Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) and propose some implementation schemas in the Spark Framework. Focusing on the setting of weight vectors, we propose two partitioning schemas, which define the distribution mode for the algorithm. The first partitioning schema is to define a partition by a group of weight vectors that are close to each other. The other schema is to distribute close weights to different partitions. Experiments in distributed framework indicate that, for most benchmarks, the schemas in distributed framework can obtain better results and better performance in expansibility.

关键词： multi-objective optimization decomposition distributed computation evolutionary algorithm

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Feature Selection with Evolving, Fast and Slow Using Two Parallel Genetic Algorithms 4

Feature Selection with Evolving, Fast and Slow Using Two Par...

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4th International Conference on Computer Science and Engineering (UBMK)

作者： Cetin, Uzay Gundogmus, Yunus Emre Istanbul Bilgi Univ Comp Engn Dept Istanbul Turkey Istanbul Marmara Univ Stat Dept Tam Faktoring Istanbul Turkey

ISBN: (纸本)9781728139647

Feature selection is one of the most challenging issues in machine learning, especially while working with high dimensional data. In this paper, we address the problem of feature selection and propose a new approach called Evolving Fast and Slow. This new approach is based on using two parallel genetic algorithms having high and low mutation rates, respectively. Evolving Fast and Slow requires a new parallel architecture combining an automatic system that evolves fast and an effortful system that evolves slow. With this architecture, exploration and exploitation can be done simultaneously and in unison. Evolving last, with high mutation rate, can be useful to explore new unknown places in the search space with long jumps;and Evolving Slow, with low mutation rate, can be useful to exploit previously known places in the search space with short movements. Our experiments show that Evolving Fast and Slow achieves very good results in terms of both accuracy and feature elimination.

关键词： Feature selection Genetic Algorithms High Di-mensional Data distributed computation Machine Learning

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distributed Computing Trade-offs with Random Connectivity

Distributed Computing Trade-offs with Random Connectivity

引用

IEEE International Symposium on Information Theory (ISIT)

作者： Srinivasavaradhan, Sundara Rajan Song, Linqi Fragouli, Christina Univ Calif Los Angeles Los Angeles CA 90095 USA

ISBN: (纸本)9781538647813

Trade-offs between distributed computation and communication are recently attracting significant interest;however, these works assume that all nodes that share the distributed computation task are within the same broadcast domain, and each can losslessly broadcast to every other node that takes part in the computation task. In this work, we dispose of this assumption, and consider the case where each node can broadcast to a subset of the nodes that take part in the computation task. We model the network via an Erdos-Renyi random graph model where a pair of nodes can communicate with each other with a probability p. We propose both uncoded and coded transmission schemes and give an achievable communication-computation tradeoff for large computational loads.

关键词： distributed computation Broadcasting Map-Reduce Communication-computation Trade-Off Random Connectivity

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Model Inversion Attacks Against Collaborative Inference 19

Model Inversion Attacks Against Collaborative Inference

引用

35th Annual Computer Security Applications Conference (ACSA)

作者： He, Zecheng Zhang, Tianwei Lee, Ruby B. Princeton Univ Princeton NJ 08544 USA Nanyang Technol Univ Singapore Singapore

ISBN: (纸本)9781450376280

The prevalence of deep learning has drawn attention to the privacy protection of sensitive data. Various privacy threats have been presented, where an adversary can steal model owners' private data. Meanwhile, countermeasures have also been introduced to achieve privacy-preserving deep learning. However, most studies only focused on data privacy during training, and ignored privacy during inference. In this paper, we devise a new set of attacks to compromise the inference data privacy in collaborative deep learning systems. Specifically, when a deep neural network and the corresponding inference task are split and distributed to different participants, one malicious participant can accurately recover an arbitrary input fed into this system, even if he has no access to other participants' data or computations, or to prediction APIs to query this system. We evaluate our attacks under different settings, models and datasets, to show their effectiveness and generalization. We also study the characteristics of deep learning models that make them susceptible to such inference privacy threats. This provides insights and guidelines to develop more privacy-preserving collaborative systems and algorithms.

关键词： Deep Neural Network Model Inversion Attack distributed computation

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distributed Swarm Evacuation Planning

Distributed Swarm Evacuation Planning

引用

IEEE Symposium on Swarm Intelligence (SIS)

作者： Merkel, Sabrina Mostaghim, Sanaz Blum, Daniel Schmeck, Hartmut Karlsruhe Inst Technol Inst AIFB D-76128 Karlsruhe Germany

ISBN: (纸本)9781467360043

This paper presents a new decentralized approach for evacuating a large number of people from a building using mobile devices which can communicate locally with each other. We investigate the impact of the local communication between the devices on the evacuation by proposing a new distributed evacuation planning algorithm called distributed Swarm Evacuation Planning. The main challenge in this approach concerns the local communication, which can be unreliable, incomplete, and delayed. Experiments show that we can significantly reduce the evacuation time compared to a modeled panic-like evacuation scenario and that the results are better than those of a shortest-path evacuation plan.

关键词： evacuation planning distributed capacity constraint routing planner swarm intelligence distributed computation

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distributed Matrix-Vector Multiplication: A Convolutional Coding Approach

Distributed Matrix-Vector Multiplication: A Convolutional Co...

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IEEE International Symposium on Information Theory (ISIT)

作者： Das, Anindya B. Ramamoorthy, Aditya Iowa State Univ Dept Elect & Comp Engn Ames IA 50010 USA

ISBN: (纸本)9781538692912

distributed computing systems are well-known to suffer from the problem of slow or failed nodes;these are referred to as stragglers. Straggler mitigation (for distributed matrix computations) has recently been investigated from the standpoint of erasure coding in several works. In this work we present a strategy for distributed matrix-vector multiplication based on convolutional coding. Our scheme can be decoded using a low-complexity peeling decoder. The recovery process enjoys excellent numerical stability as compared to Reed-Solomon coding based approaches (which exhibit significant problems owing their badly conditioned decoding matrices). Finally, our schemes are better matched to the practically important case of sparse matrix-vector multiplication as compared to many previous schemes. Extensive simulation results corroborate our findings.

关键词： distributed computation Stragglers Cross Parity Check Convolutional Code Reed-Solomon Coding

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Efficient Coded distributed Computing via Joint Cellular and D2D Communications

Efficient Coded Distributed Computing via Joint Cellular and...

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IEEE International Conference on Communications (ICC)

作者： Tu, Haoyu Zai, Qixuan Li, Chenglin Wu, Youlong ShanghaiTech Univ Sch Informat Sci & Technol Shanghai Peoples R China

ISBN: (数字)9781538683477

ISBN: (纸本)9781538683477

This paper tackles the distributed computing problem in a joint cellular and device-to-device (D2D) network, where edge users can exchange information both through an access point (e.g., base station) and D2D communication links. The D2D network consists of multiple disjoint clusters, where multiple users can transmit signals simultaneously to their neighbouring users within the same cluster, due to disjoint connections between clusters. A nested coded distributed computation (CDC) scheme is proposed to reduce the communication load both in the uplink and downlink communication, by leveraging coding techniques and parallel transmission opportunities in the D2D network. It is shown that this scheme is optimal in the sense that it achieves the minimum communication load both in the uplink and downlink. The nested CDC scheme can also reduce the coding complexity, compared with the conventional wireless CDC scheme proposed by Li et al., whose computational complexity grows exponentially with the computation load.

关键词： distributed computation Communication D2D

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Multi-User Linearly Separable computation: A Coding Theoretic Approach

Multi-User Linearly Separable Computation: A Coding Theoreti...

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IEEE Information Theory Workshop (ITW)

作者： Khalesi, Ali Elia, Petros Eurecom F-06410 Sophia Antipolis France

ISBN: (数字)9781665483414

ISBN: (纸本)9781665483414

In this work, we investigate the problem of multiuser linearly separable function computation, where N servers help compute the desired functions (jobs) of K users. In this setting each desired function can be written as a linear combination of up to L (generally non-linear) sub-functions. Each server computes some of the sub-tasks, and communicates a linear combination of its computed outputs (files) in a singleshot to some of the users, then each user linearly combines its received data in order to recover its desired function. We explore the range of the optimal computation cost via establishing a novel relationship between our problem, syndrome decoding and covering codes. The work reveals that in the limit of large N, the optimal computation cost - in the form of the maximum fraction of all servers that must compute any subfunction - is lower bounded as gamma >= II (-1) (q) ( log q (L)/N), for any fixed log q(L)/N. The result reveals the role of the computational rate log q (L)/N, which cannot exceed what one might call the computational capacity Hq(gamma) of the system.

关键词： distributed computation Linearly separable function Coding theory

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Mitigating Server Breaches in Password-Based Authentication: Secure and Efficient Solutions

Mitigating Server Breaches in Password-Based Authentication:...

引用

Cryptographers Track at the RSA Conference (CT-RSA)

作者： Blazy, Olivier Chevalier, Celine Vergnaud, Damien Univ Limoges XLim Limoges France Univ Pantheon Assas Paris France INRIA CNRS ENS Paris France PSL Res Univ Paris France

ISBN: (纸本)9783319294858;9783319294841

Password-Authenticated Key Exchange allows users to generate a strong cryptographic key based on a shared "human-memorable" password without requiring a public-key infrastructure. It is one of the most widely used and fundamental cryptographic primitives. Unfortunately, mass password theft from organizations is continually in the news and, even if passwords are salted and hashed, brute force breaking of password hashing is usually very successful in practice. In this paper, we propose two efficient protocols where the password database is somehow shared among two servers (or more), and authentication requires a distributed computation involving the client and the servers. In this scenario, even if a server compromise is doable, the secret exposure is not valuable to the adversary since it reveals only a share of the password database and does not permit to brute force guess a password without further interactions with the parties for each guess. Our protocols rely on smooth projective hash functions and are proven secure under classical assumption in the standard model (i.e. do not require idealized assumption, such as random oracles).

关键词： Password-authenticated key exchange distributed computation Decision diffie-hellman Smooth projective hashing

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Large-Scale Complex Systems: From Antenna Circuits to Power Grids

Large-Scale Complex Systems: From Antenna Circuits to Power ...

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作者： Lavaei, Javad California Institute of Technology

学位级别：Ph.D.

This dissertation is motivated by the lack of scalable methods for the analysis and synthesis of different large-scale complex systems appearing in electrical and computer engineering. The systems of interest in this work are power networks, analog circuits, antenna systems, communication networks and distributed control systems. By combining theories from control and optimization, the high-level objective is to develop new design tools and algorithms that explicitly exploit the physical properties of these practical systems (e.g., passivity of electrical elements or sparsity of network topology). To this end, the aforementioned systems are categorized intro three classes of systems, and then studied in Parts I, II, and III of this dissertation, as explained below: Power networks: In Part I of this work, the operation planning of power networks using efficient algorithms is studied. The primary focus is on the optimal power flow (OPF) problem, which has been studied by the operations research and power communities in the past 50 years with little success. In this part, it is shown that there exists an efficient method to solve a practical OPF problem along with many other energy-related optimization problems such as dynamic OPF or security-constrained OPF. The main reason for the successful convexification of these optimization problems is also identified to be the physical properties of a power circuit, especially the passivity of transmission lines. Circuits and systems: Motivated by different applications in power networks, electromagnetics and optics, Part II of this work studies the fundamental limits associated with the synthesis of a particular type of linear circuit. It is shown that the optimal design of the parameters of this type of circuit can be performed in polynomial time if the circuit is passive and there are sufficient number of controllable (unknown) parameters. This result introduces a trade-off between the design simplicity and the implementatio

关键词： Convex Optimization Power Networks Communication Networks distributed computation Smart Grid Control

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