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31st International Conference on Machine Learning, ICML 2014

作者： Yan, Ling Li, Wu-Jun Xue, Gui-Rong Han, Dingyi Department of Computer Science and Engineering Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University China Department of Computer Science and Technology National Key Laboratory for Novel Software Technology Nanjing University China Alibaba Group China

ISBN: (纸本)9781634393973

In display advertising, click through rate (CTR) prediction is the problem of estimating the probability that an advertisement (ad) is clicked when displayed to a user in a specific context. Due to its easy implementation and promising performance, logistic regression (LR) model has been widely used for CTR prediction, especially in industrial systems. However, it is not easy for LR to capture the nonlinear information, such as the conjunction information, from user features and ad features. In this paper, we propose a novel model, called coupled group lasso (CGL), for CTR prediction in display advertising. CGL can seamlessly integrate the conjunction information from user features and ad features for modeling. Furthermore, CGL can automatically eliminate useless features for both users and ads, which may facilitate fast online prediction. Scalability of CGL is ensured through feature hashing and distributed implementation. Experimental results on real-world data sets show that our CGL model can achieve state-of-the-art performance on web- scale CTR prediction tasks. Copyright © (2014) by the International Machine Learning Society (IMLS) All rights reserved.

关键词： Forecasting

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Distributed stochastic ADMM for matrix factorization 14

Distributed stochastic ADMM for matrix factorization

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23rd ACM International Conference on Information and Knowledge Management, CIKM 2014

作者： Yu, Zhi-Qin Shi, Xing-Jian Yan, Ling Li, Wu-Jun Shanghai Key Laboratory of Scalable Computing and Systems Department of Computer Science and Engineering Shanghai Jiao Tong University China Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong National Key Laboratory for Novel Software Technology Department of Computer Science and Technology Nanjing University China

ISBN: (纸本)9781450325981

Matrix factorization (MF) has become the most popular technique for recommender systems due to its promising performance. Recently, distributed (parallel) MF models have received much attention from researchers of big data community. In this paper, we propose a novel model, called distributed stochastic alternating direction methods of multipliers (DS-ADMM), for large-scale MF problems. DS-ADMM is a distributed stochastic variant of ADMM. In particular, we first devise a new data split strategy to make the distributed MF problem fit for the ADMM framework. Then, a stochastic ADMM scheme is designed for learning. Finally, we implement DS-ADMM based on message passing interface (MPI), which can run on clusters with multiple machines (nodes). Experiments on several data sets from recommendation applications show that our DS-ADMM model can outperform other state-of-the-art distributed MF models in terms of both efficiency and accuracy. Copyright 2014 ACM.

关键词： Recommender systems

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CIRF: Constructive interference-based reliable flooding in asynchronous duty-cycle wireless sensor networks

CIRF: Constructive interference-based reliable flooding in a...

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IEEE Conference on Wireless Communications and Networking

作者： Shuying Yu Xiaobing Wu Pan Wu Dingming Wu Haipeng Dai Guihai Chen National Key Laboratory for Novel Software Technology Nanjing University Nanjing China Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781479930845

Flooding is one of the most fundamental functions in wireless sensor networks (WSNs) and has been investigated extensively. Existing flooding schemes in duty-cycle WSNs can be categorized into two categories: synchronous ones and asynchronous ones. In practice asynchronous schemes are preferable since synchronous ones introduce more complexity and overhead for necessary clock synchronization. Existing asynchronous approaches are however imperfect for reliable flooding in duty-cycle WSNs. For example, opportunistic flooding is less flexible and Asynchronous Duty-cycle Broadcasting (ADB) suffers unsatisfactory flooding latency. We propose Constructive Interference-based Reliable Flooding (CIRF) in this paper, a novel design for reliable flooding in asynchronous duty-cycle WSNs. CIRF is integrated with the MAC protocol Receiver-Initiated MAC (RI-MAC) to improve the utilization of wireless medium and guarantee one-hop reliable transmission. The key idea of CIRF is to exploit the constructive interference feature when concurrent transmission occurs, which can be common in RI-MAC based WSNs. Simulation results indicate that CIRF achieves reliable flooding with reduced flooding latency, higher energy efficiency and delivery ratio compared to existing schemes.

关键词： Wireless sensor networks Interference Reliability Delays Receivers Floods Wireless communication

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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On pricing schemes in data center network with game theoretic approach

On pricing schemes in data center network with game theoreti...

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International Conference on Computer Communications and Networks (ICCCN)

作者： Hao Wang Yangming Zhao Haibing Guan Shanghai Key Laboratory of Scalable Computing and Systems SJTU Shanghai P. R. China School of Communication and Information Engineering UESTC Chengdu P. R. China

This paper aims at systematically analyzing the pricing schemes in data center network. The interaction between a monopolistic operator and customers in the network is modeled as Stackelberg game. In this model, both homogeneous- and heterogeneous-customer scenarios are analyzed. In homogeneous customer case, a special scenario is that only a single customer exists in the network. In this scenario, we observe that the Stackelberg equilibrium will lead to a Pareto-inefficient outcome. To address this problem, a two-part pricing scheme is proposed to derive a Pareto efficient outcome and benefit both the operator and customers. When there are an infinite number of homogeneous customers in the network, our analysis shows that customers' selfish action may incur zero utility to them and operator can achieve all the utility by announcing an appropriate price. As to the heterogeneous customer case, we not only analyse how the operator should price the network resources, but also introduce Paris Metro Pricing (PMP) scheme to further increase operator's profit. Since the operator's profit is not a concave function of the resource price, these studies are conducted by simulation.

关键词： Quality of service Pricing Games Lead Equations Analytical models Economics

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25th Annual Computational Neuroscience Meeting CNS-2016, Seogwipo City, South Korea, July 2-7, 2016 Abstracts

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BMC NEUROSCIENCE 2016年第1期17卷 1-112页

作者： [Anonymous] Computational Neurobiology Laboratory The Salk Institute for Biological Studies San Diego USA UNIC CNRS Gif sur Yvette France The European Institute for Theoretical Neuroscience (EITN) Paris France ATR Computational Neuroscience Laboratories Kyoto Japan Krembil Research Institute University Health Network Toronto Canada Department of Physiology University of Toronto Toronto Canada Department of Medicine (Neurology) University of Toronto Toronto Canada Department of Physics University of New Hampshire Durham USA Department of Neurophysiology Nencki Institute of Experimental Biology Warsaw Poland Department of Theory Wigner Research Centre for Physics of the Hungarian Academy of Sciences Budapest Hungary Department of Mathematical Sciences KAIST Daejoen Republic of Korea Department of Mathematics University of Houston Houston USA Department of Biochemistry & Cell Biology and Institute of Biosciences and Bioengineering Rice University Houston USA Department of Biology and Biochemistry University of Houston Houston USA Grupo de Neurocomputación Biológica Dpto. de Ingeniería Informática Escuela Politécnica Superior Universidad Autónoma de Madrid Madrid Spain Department of Biological Sciences University of Southern California Los Angeles USA Center for Neuroscience Korea Institute of Science and Technology Seoul South Korea Department of Neurology Albert Einstein College of Medicine Bronx USA Center for Neuroscience KIST Seoul South Korea Department of Neuroscience University of Science and Technology Daejon South Korea Systems Neuroscience Group QIMR Berghofer Medical Research Institute Herston Australia Department of Psychology Yonsei University Seoul South Korea Department of Psychiatry Kyung Hee University Hospital at Gangdong Seoul South Korea Department of Psychiatry Veterans Administration Boston Healthcare System and Harvard Medical School Brockton USA Department of Electrical and Electronic Engineering The University of Melbourne Parkvil

A1 Functional advantages of cell-type heterogeneity in neural circuits Tatyana O. Sharpee A2 Mesoscopic modeling of propagating waves in visual cortex Alain Destexhe A3 Dynamics and biomarkers of mental disorders Mitsuo Kawato F1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons Vladislav Sekulić, Frances K. Skinner F2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brains Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári F3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks. Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir Josić O1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generators Irene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo Varona O2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrain Eunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun Choi O3 Modeling auditory stream segregation, build-up and bistability James Rankin, Pamela Osborn Popp, John Rinzel O4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fields Alejandro Tabas, André Rupp, Emili Balaguer-Ballester O5 A simple model of retinal response to multi-electrode stimulation Matias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish Meffin O6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination task Veronika Koren, Timm Lochmann, Valentin Dragoi, Klaus Obermayer O7 Input-location dependent gain modulation in cerebellar nucleus neurons Maria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Ni

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kMemvisor: Flexible system wide memory mirroring in virtual environments

kMemvisor: Flexible system wide memory mirroring in virtual ...

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22nd ACM International Symposium on High-Performance Parallel and Distributed computing, HPDC 2013

作者： Wang, Bin Qi, Zhengwei Guan, Haibing Dong, Haoliang Sun, Wei Dong, Yaozu Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University Shanghai China School of Software Shanghai Jiao Tong University Shanghai China Intel China Software Center Shanghai China

ISBN: (纸本)9781450319102

Today's commercial cloud service providers require the availability with an annual uptime percentage at least 99.95%. While memory errors become norms instead of exceptions with the increasing memory's density and capacity in cloud applications. Thus, uncorrected errors from DRAM can be a significant source of system downtime. To address this increasingly important concern, both hardware and software memory mirroring technologies are studied nowadays to provide memory high availability. However, hardware solutions like mirror memory, which uses doubled chip, need dedicated and costly peripheral hardware. While existing software approaches, i.e., virtual machine's checkpoint technology, reduce the expense but incur the high overhead in practical usage. In this paper, we present a novel system called kMemvisor to provide system-wide high availability memory mirroring. It is a software approach achieving flexible multi-granularity memory mirroring via virtualization and binary translation technology. Specifically, kMemvisor first creates backup space of the same size of the specified memory for applications or virtual machines. We can flexibly set memory areas to be mirrored or not mirrored from application level to system-wide. Then, all memory write instructions in the native memory space are captured and instrumented by mirror memory write instructions to synchronize the data in backup space. Furthermore, this instruction level memory synchronization reduces backup overhead and lowers the probability of data loss compared with traditional software approaches. So kMemvisor could use data from the backup space to recover when memory failures happen. The results show that kMemvisor causes 55% overhead in the worst case of system-wide high availability and 30% average for the real world applications, which outperforms the state-of-the-art software approaches even in the worst case. © 2013 ACM.

关键词： Virtual machine

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Fuzzy clustering with multi-resolution bilateral filtering for medical image segmentation

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International Journal of Fuzzy System Applications 2013年第4期3卷 47-59页

作者： Xiao, Kai Li, Jianli Xiao, Shuangjiu Guan, Haibing Fang, Fang Hassanien, Aboul Ella School of Software Shanghai Jiaotong University Shanghai China Shanghai Key Laboratory of Scalable Computing and Systems Department of Computer Science Shanghai Jiaotong University Shanghai China Shanghai First People's Hospital Shanghai China Department of Information Technology Cairo University Giza Cairo Egypt

Although fuzzy c-means (FCM) algorithm and some of its variants have been extensively widely used in unsupervised medical image segmentation applications in recent years, they more or less suffer from either noise sensitivity or loss of details, which always is a key point to medical image processing. This paper presents a novel FCM variation method that is suitable for medical image segmentation. The proposed method, typically by incorporating multi-resolution bilateral filter which is combined with wavelet thresholding, provides the following advantages: (1) it is less sensitive to both high- and low-frequency noise and removes spurious blobs and noisy spots, (2) it yields more homogeneous clustering regions, and (3) it preserves detail, thus significantly improving clustering performance. By the use of synthetic and multiple-feature magnetic resonance (MR) image data, the experimental results and quantitative analyses suggest that, compared to other fuzzy clustering algorithms, the proposed method further enhances the robustness to noisy images and capacity of detail preservation. Copyright © 2013, IGI Global.

关键词： Fuzzy clustering

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Using minimum mobile chargers to keep large-scale wireless rechargeable sensor networks running forever

Using minimum mobile chargers to keep large-scale wireless r...

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2013 IEEE 2013 22nd International Conference on Computer Communication and Networks, ICCCN 2013

作者： Dai, Haipeng Wu, Xiaobing Xu, Lijie Chen, Guihai Lin, Shan State Key Laboratory for Novel Software Technology Nanjing University Nanjing Jiansu 210046 China Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University Shanghai 200240 China Temple University Philadelphia PA United States

ISBN: (纸本)9781467357746

Wireless Rechargeable Sensor Networks (WRSNs) can be recharged after deployment for sustainable operations. Recent works propose to use a single mobile charger (MC) traveling through the network fields to recharge every sensor node. These algorithms work well in small scale networks. However, in large scale networks these algorithms do not work efficiently, especially when the amount of energy the MC can provide is limited. To address these challenges, multiple MCs can be used. In this paper, we investigate the minimum MCs problem (MinMCP) for rechargeable sensor networks: how to find the minimum number of energy-constrained MCs and design their recharging routes given a sensor network such that each sensor node in the WRSN maintains continuous work. Our results are three folds. We first prove that for any Ε > 0, there is no (2-Ε)-approximation algorithm for Distance Constrained Vehicle Routing Problem (DVRP) on a general metric space, which is the best as far as we know. By reducing from DVRP, we prove that MinMCP is NP-hard, and the inapproximability bound for MinMCP is the same as that of DVRP. Then we propose approximation algorithms for this problem. Finally, we conduct simulations to validate the effectiveness of our algorithms. © 2013 IEEE.

关键词： Approximation algorithms

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COLO: COarse-grained LOck-stepping virtual machines for non-stop service

COLO: COarse-grained LOck-stepping virtual machines for non-...

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4th Annual Symposium on Cloud computing, SoCC 2013

作者： Dong, Yaozu Ye, Wei Jiang, Yunhong Pratt, Ian Ma, Shiqing Li, Jian Guan, Haibing Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University China Intel Asia-Pacific R and D Ltd. China School of Software Shanghai Jiao Tong University China Bromium Inc. United States

ISBN: (纸本)9781450324281

Virtual machine (VM) replication provides a software solution of for business continuity and disaster recovery through application-agnostic hardware fault tolerance by replicating the state of primary VM (PVM) to secondary VM (SVM) on a different physical node. Unfortunately, current VM replication approaches suffer from excessive overhead, which severely limit their applicability and suitability. In this paper, we leverage the practical effect of networked server-client system that PVM and SVM are considered as in the same state only if they can generate the same response from the clients' point of view, and this is exploited to optimize performance. To this end, we propose a generic and highly efficient non-stop service solution, named as "COLO" (COarse-grained LOck-stepping virtual machine) utilizing on-demand VM replication. COLO monitors the output responses of the PVM and SVM, and rules the SVM as a valid replica of the PVM according to the output similarity between PVM and SVM. If the responses do not match, the commit of network response is withheld until PVM's state has been synchronized to SVM. Hence, we ensure that the system is always capable of failover by SVM. Although non-determinism may mean a different internal state of SVM from that of the PVM, it is equally valid and remains consistent from external observations. Unlike earlier instruction level lock-stepping deterministic execution approaches, COLO can easily support Multi-Processors (MP) involving workloads with the satisfying performance. Results show that COLO significantly outperforms existing approaches, particularly on server-client workloads such as online databases and web server applications. Copyright © 2013 by the Association for computing Machinery, Inc.

关键词： Virtual machine

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