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检索条件"主题词=Algorithm Design And Analysis"

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Modeling of Joint Synergy and Spasticity in Stroke Patients to Solve Arm Reach Tasks

Modeling of Joint Synergy and Spasticity in Stroke Patients ...

引用

IEEE Signal Processing in Medicine and Biology Symposium (SPMB)

作者： Feldman, A. Shen, Y. Rosen, J. Univ Calif Los Angeles Bion Lab Los Angeles CA 90095 USA

ISBN: (纸本)9781538648735

Neurological damage caused by stroke can result in motor control impairments [1] such as deleterious joint synergies (involuntary coactivation of joints) and spasticity (involuntary muscular contractions that limit range of motion). These issues reduce the arm workspace. necessitating modified rehabilitation training methods. Task-specific therapies that simulate activities of daily living (ADL) can be used to relearn the requisite motions [2]. However. individuals with joint synergy and spasticity may not know how to complete daily living tasks while compensating for their motor issues. This research focuses on developing an algorithm that finds efficient reach paths by taking into account the joint synergy and spasticity. In addition to helping patients complete ADLs, the algorithm could serve as a tool for classifying the feasibility and painfulness of reach tasks.

关键词： Jacobian matrices Classification algorithms algorithm design and analysis Robots Frequency modulation Biomimetics

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Accelerated Hierarchical Density Based Clustering 17

Accelerated Hierarchical Density Based Clustering

引用

17th IEEE International Conference on Data Mining (ICDMW)

作者： McInnes, Leland Healy, John Corvidae Technology (HK) Limited Hong Kong Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong

ISBN: (纸本)9781538638002

We present an accelerated algorithm for hierarchical density based clustering. Our new algorithm improves upon HDBSCAN*, which itself provided a significant qualitative improvement over the popular DBSCAN algorithm. The accelerated HDBSCAN* algorithm provides comparable performance to DBSCAN, while supporting variable density clusters, and eliminating the need for the difficult to tune distance scale parameter epsilon. This makes accelerated HDBSCAN* the default choice for density based clustering.

关键词： Clustering algorithms algorithm design and analysis Robustness Couplings Density functional theory Data analysis Acceleration

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Force-Directed Scheduling for Data Flow Graph Mapping on Coarse-Grained Reconfigurable Architectures

Force-Directed Scheduling for Data Flow Graph Mapping on Coa...

引用

2014 International Conference on Reconfigurable Computing and FAGAs

作者： Fell, Alexander Rakossy, Zoltan Endre Chattopadhyay, Anupam Indraprastha Inst Informat Technol New Delhi India Rhein Westfal TH Aachen Inst Commun Technol & Embedded Syst ICE Aachen Germany Nanyang Technol Univ Sch Comp Engn Singapore Singapore

ISBN: (纸本)9781479959440

In terms of energy and flexibility, Coarse-Grained Reconfigurable Architectures (CGRA) are proven to be advantageous over fine-grained architectures, massively parallel GPUs and generic CPUs. However the key challenge of programmability is preventing wide-spread adoption. To exploit instruction level parallelism inherent to such architectures, optimal scheduling and mapping of algorithmic kernels is essential. Transforming an input algorithm in the form of a Data Flow Graph (DFG) into a CGRA schedule and mapping configuration is very challenging, due the necessity to consider architectural details such as memory bandwidth requirements, communication patterns, pipelining and heterogeneity to optimally extract maximum performance. In this paper, an algorithm is proposed that employs Force-Directed Scheduling concepts to solve such scheduling and resource minimization problems. Our heuristic extensions are flexible enough for generic heterogeneous CGRAs, allowing to estimate the execution time of an algorithm with different configurations, while maximizing the utilization of available hardware. Beside our experiments, we compare also given CGRA configurations introduced by state-of-the-art mapping algorithms such as EPIMap, achieving optimal resource utilization by our schedule with a reduced overall DFG execution time by 39% on average.

关键词： data flow computing reconfigurable architectures resource allocation scheduling CGRA DFG coarse-grained reconfigurable architecture data flow graph mapping force-directed scheduling resource minimization algorithm design and analysis Fabrics Hardware Indexes Pipelines Schedules Scheduling

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Secure Network Monitoring Using Programmable Data Planes

Secure Network Monitoring Using Programmable Data Planes

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IEEE Conference Network Function Virtualization and Software Defined Networks (NFV-SDN)

作者： Pereira, Fabio Neves, Nuno Ramos, Fernando M. V. Univ Lisbon Fac Ciencias LaSIGE Lisbon Portugal

ISBN: (纸本)9781538632857

The accuracy provided by traditional sampling-based monitoring approaches, such as NetFlow, is increasingly being considered insufficient to meet the requirements of today's networks. By summarizing all traffic for specific statistics of interest, sketch-based alternatives have been shown to achieve higher levels of accuracy for the same cost. Existing switches, however, lack the necessary capability to perform the sort of processing required by this approach. The emergence of programmable switches and the processing they enable in the data plane has recently led sketch-based solutions to be made possible in switching hardware. One limitation of existing solutions is that they lack security. At the scale of the datacenter networks that power cloud computing, this limitation becomes a serious concern. For instance, there is evidence of security incidents perpetrated by malicious insiders inside cloud infrastructures. By compromising the monitoring algorithm, such an attacker can render the monitoring process useless, leading to undesirable actions (such as routing sensitive traffic to disallowed locations). In this paper we propose, for the first time, a secure sketch-based monitoring solution that can run in programmable switches. Our algorithm - a secure version of the well-known count-min sketch - was implemented in P4, a programming language for switches. The evaluation of our solution demonstrates the performance penalty introduced by security to be negligible.

关键词： Monitoring Data structures Security algorithm design and analysis Prediction algorithms Estimation

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High Quality and Efficient Light Field Image Rendering Based on White Image Compensation 4

High Quality and Efficient Light Field Image Rendering Based...

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IEEE International Conference on Consumer Electronics - Taiwan (ICCE-TW)

作者： Hsu, Chia-Chun Ding, Jian-Jiun Natl Taiwan Univ Grad Inst Commun Engn Taipei Taiwan

ISBN: (纸本)9781509040179

Image rendering is an important technique in light filed image processing. It is to reconstruct the entire scene by combining micro images. However, due to the imperfect optical design of the light field camera, micro images suffer from the attenuation effect, which causes server blocking artifacts in the final rendered image. In this work, a high quality and efficient image rendering algorithm based on the linear blending and white image compensation is proposed. First, the compensation model is estimated from the white image. Then, an adaptive modified function is adopted to adjust the compensation rate. Finally, the light field image can be reconstructed by applying the linear blending technique. Simulations show that the proposed light field image rendering algorithm is able to reconstruct a high quality light field image with less artifacts than existing methods.

关键词： Rendering (computer graphics) Image reconstruction Attenuation algorithm design and analysis Adaptation models Estimation Cameras

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Treelogy: A Benchmark Suite for Tree Traversals

Treelogy: A Benchmark Suite for Tree Traversals

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IEEE International Symposium on Performance analysis of Systems and Software (ISPASS)

作者： Hegde, Nikhil Liu, Jianqiao Sundararajah, Kirshanthan Kulkarni, Milind Purdue Univ Sch Elect & Comp Engn W Lafayette IN 47907 USA

ISBN: (纸本)9781538638903

An interesting class of irregular algorithms is tree traversal algorithms, which repeatedly traverse various trees to perform efficient computations. Tree traversal algorithms form the algorithmic kernels in an important set of applications in scientific computing, computer graphics, bioinformatics, and data mining, etc. There has been increasing interest in understanding tree traversal algorithms, optimizing them, and applying them in a wide variety of settings. Crucially, while there are many possible optimizations for tree traversal algorithms, which optimizations apply to which algorithms is dependent on algorithmic characteristics. In this work, we present a suite of tree traversal kernels, drawn from diverse domains, called Treelogy, to explore the connection between tree traversal algorithms and state-of-the-art optimizations. We characterize these algorithms by developing an ontology based on their structural properties. The attributes extracted through our ontology, for a given traversal kernel, can aid in quick analysis of the suitability of platform- and application-specific as well as independent optimizations. We provide reference implementations of these kernels for three platforms: shared memory multicores, distributed memory systems, and GPUs, and evaluate their scalability.

关键词： Optimization Kernel Ontologies Benchmark testing Correlation algorithm design and analysis Data mining

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Locally Self-Adjusting Skip Graphs 37

Locally Self-Adjusting Skip Graphs

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37th IEEE International Conference on Distributed Computing Systems (ICDCS)

作者： Huq, Sikder Ghosh, Sukumar Univ Iowa Dept Comp Sci Iowa City IA 52242 USA

ISBN: (纸本)9781538617915

We present a distributed self-adjusting algorithm for skip graphs that minimizes the average routing costs between arbitrary communication pairs by performing topological adaptation to the communication pattern. Our algorithm is fully decentralized, conforms to the CONGEST model (i.e. uses O(log n) bit messages), and requires O(log n) bits of memory for each node, where n is the total number of nodes. Upon each communication request, our algorithm first establishes communication by using the standard skip graph routing, and then locally and partially reconstructs the skip graph topology to perform topological adaptation. We propose a computational model for such algorithms, as well as a yardstick (working set property) to evaluate them. Our working set property can also be used to evaluate self-adjusting algorithms for other graph classes where multiple tree-like subgraphs overlap (e.g. hypercube networks). We derive a lower bound of the amortized routing cost for any algorithm that follows our model and serves an unknown sequence of communication requests. We show that the routing cost of our algorithm is at most a constant factor more than the amortized routing cost of any algorithm conforming to our computational model. We also show that the expected transformation cost for our algorithm is at most a logarithmic factor more than the amortized routing cost of any algorithm conforming to our computational model.

关键词： Peer-to-peer computing Computational modeling algorithm design and analysis Routing Heuristic algorithms Topology Data structures

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On the Delivery of Augmented Information Services over Wireless Computing Networks

On the Delivery of Augmented Information Services over Wirel...

引用

IEEE International Conference on Communications (ICC) / Wireless Communications Symposium / 3rd Workshop on Optical Wireless Communications (OWC)

作者： Feng, Hao Llorca, Jaime Tulino, Antonia M. Molisch, Andreas F. Univ Southern Calif Los Angeles CA 90007 USA Nokia Bell Labs Murray Hill NJ 07974 USA Univ Naples Federico II Naples Italy

ISBN: (纸本)9781467389990

In an augmented information (AgI) service, users consume information that results from the execution of a chain of service functions that process source information to create real-time augmented value. Applications may include real-time analysis of remote sensing data, real-time computer vision, personalized video streaming, and augmented reality, among others. We consider the problem of optimal distribution of AgI services over a wireless computing network, in which nodes are equipped with both communication and computing resources. We characterize the wireless computing network capacity region and design a joint flow scheduling and resource allocation algorithm that stabilizes the underlying queuing system while achieving arbitrarily close to minimum network cost, with a tradeoff in network delay. Our solution captures the unique chaining and flow scaling aspects of AgI services, while exploiting the use of the broadcast approach over the wireless channel.

关键词： Wireless communication Ad hoc networks Cloud computing Resource management Wireless sensor networks Real-time systems algorithm design and analysis

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Preventing False Discovery in Interactive Data analysis is Hard 55

Preventing False Discovery in Interactive Data Analysis is H...

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55th Annual IEEE Symposium on Foundations of Computer Science (FOCS)

作者： Hardt, Moritz Ullman, Jonathan IBM Res Almaden San Jose CA 95120 USA Harvard Univ Sch Engn & Appl Sci Cambridge MA 02138 USA Harvard Univ Ctr Res Computat & Soc Cambridge MA 02138 USA

ISBN: (纸本)9781479965175

We show that, under a standard hardness assumption, there is no computationally efficient algorithm that given n samples from an unknown distribution can give valid answers to n(3+0(1)) adaptively chosen statistical queries. A statistical query asks for the expectation of a predicate over the underlying distribution, and an answer to a statistical query is valid if it is "close" to the correct expectation over the distribution. Our result stands in stark contrast to the well known fact that exponentially many statistical queries can be answered validly and efficiently if the queries are chosen non-adaptively (no query may depend on the answers to previous queries). Moreover, Dwork et al. [1], showed how to accurately answer exponentially many adaptively chosen statistical queries via a computationally inefficient algorithm. They also gave efficient algorithm that can answer nearly n(2) adaptively chosen queries, which shows our result is almost quantitatively tight. Conceptually, our result demonstrates that achieving statistical validity alone can be a source of computational intractability in adaptive settings. For example, in the modern large collaborative research environment, data analysts typically choose a particular approach based on previous findings. False discovery occurs if a research finding is supported by the data but not by the underlying distribution. While the study of preventing false discovery in Statistics is decades old, to the best of our knowledge our result is the first to demonstrate a computational barrier. In particular, our result suggests that the perceived difficulty of preventing false discovery in today's collaborative research environment may be inherent.

关键词： Accuracy Adaptation models algorithm design and analysis Encryption Polynomials Privacy Standards algorithm design and analysis cryptography False-positives Privacy Polynomial Adaptation models efficient algorithm Answer Data analysis

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Learning Distributed Representations for Large-Scale Dynamic Social Networks

Learning Distributed Representations for Large-Scale Dynamic...

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IEEE Conference on Computer Communications (IEEE INFOCOM)

作者： Zhiyuli, Aakas Liang, Xun Xu, Zhiming Renmin Univ China Sch Informat Beijing 100872 Peoples R China

ISBN: (纸本)9781509053360

Learning distributed representations of symbolic data were introduced by Hinton[1], and first developed in modeling networks for learning the node vectors by Perozzi et al (2014). In this work, we proposed DNPS, a novel nodes embedding approach for acquiring distributed representations of large-scale dynamic social networks. DNPS is suitable for many types of social networks: dynamic/static, directed/undirected, and weighted/unweighted. Recently, several works of nodes embedding were proposed. However, they were designed for static networks, such as language networks. To address this problem, first, we develop a damping based positive sampling (DPS) algorithm to learn the hierarchical structure of social networks. Then, we devise a local search based DPS algorithm to obtain incremental information of network evolution. Finally, we show DNPS's potentials on future link prediction task for three real-life large-scale dynamic social networks. The results show that DNPS consistently outperforms all baseline methods and exhibits an improvement of 12%, 6%, 4% on DIGG, FLICKR and YOUTUBE over the second-highest level, respectively. Moreover, DNPS is also scalable. For example, DNPS can speed up the training process in 2 similar to 36 times compared with benchmarks on FLICKR network. The source codes of the project is available online(1).

关键词： Social network services Damping Heuristic algorithms Training algorithm design and analysis Prediction algorithms Conferences

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