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检索条件"主题词=Algorithm design and analysis"

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Multi-level Feedback Web Links Selection Problem: Learning and Optimization 17

Multi-level Feedback Web Links Selection Problem: Learning a...

引用

17th IEEE International Conference on Data Mining (ICDMW)

作者： Cai, Kechao Chen, Kun Huang, Longbo Lui, John C. S. Chinese Univ Hong Kong Dept Comp Sci & Engn Hong Kong Hong Kong Peoples R China Tsinghua Univ Inst Interdisciplinary Informat Sci IIIS Beijing Peoples R China

ISBN: (纸本)9781538638354

Selecting the right web links for a website is important because appropriate links not only can provide high attractiveness but can also increase the website's revenue. In this work, we first show that web links have an intrinsic multi-level feedback structure. For example, consider a 2-level feedback web link: the 1st level feedback provides the Click-Through Rate (CTR) and the 2nd level feedback provides the potential revenue, which collectively produce the compound 2-level revenue. We consider the context-free links selection problem of selecting links for a homepage so as to maximize the total compound 2-level revenue while keeping the total 1st level feedback above a preset threshold. We further generalize the problem to links with n (n = 2)-level feedback structure. The key challenge is that the links' multi-level feedback structures are unobservable unless the links are selected on the homepage. To our best knowledge, we are the first to model the links selection problem as a constrained multi-armed bandit problem and design an effective links selection algorithm by learning the links' multi-level structure with provable sub-linear regret and violation bounds. We uncover the multi-level feedback structures of web links in two real-world datasets. We also conduct extensive experiments on the datasets to compare our proposed LExp algorithm with two state-of-the-art context-free bandit algorithms and demonstrate that LExp algorithm is the most effective in links selection while satisfying the constraint.

关键词： Compounds Web pages algorithm design and analysis Probabilistic logic Stochastic processes Knowledge engineering Random processes

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Eliminating a Hidden Error Source in Stochastic Circuits 13

Eliminating a Hidden Error Source in Stochastic Circuits

引用

IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT)

作者： Ting, Paishun Hayes, John P. Univ Michigan Dept Elect Engn & Comp Sci Ann Arbor MI 48109 USA

ISBN: (纸本)9781538603628

Stochastic computing (SC) computes with probabilities using random bit-streams and standard logic circuits. Its advantages are ultra-low area and power, coupled with high error tolerance. However, due to its randomness features, SC's accuracy is often low and hard to control, thus severely limiting its practical applications. Random fluctuation errors (RFEs) in SC data are a major factor affecting accuracy, and are usually addressed by increasing the bit-stream length N. However, increasing N can result in excessive computation time and energy consumption, counteracting the main advantages of SC. In this work, we first observe that many SC designs heavily rely on constant inputs, which contribute significantly to RFEs. We then investigate the role of constant inputs in SC, and propose a systematic algorithm CEASE to eliminate them by introducing memory into the target circuits. We provide analytical and experimental results which demonstrate that CEASE is optimal in terms of minimizing RFEs.

关键词： Radio frequency Adders Fluctuations algorithm design and analysis Energy consumption Systematics Boolean functions

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Visual simulator for MavLink-protocol-based UAV, applied for search and analyze task

Visual simulator for MavLink-protocol-based UAV, applied for...

引用

Federated Conference on Computer Science and Information Systems (FedCSIS)

作者： Smigielski, Piotr Raczynski, Mateusz Gosek, Lukasz AGH Univ Sci & Technol Fac Automat Elect Engn Comp Sci & Biomed Engn Student Sci Assoc AI LAB Al Mickiewicza 30 PL-30059 Krakow Poland

ISBN: (纸本)9788394625375

In this paper the authors present the results of research to develop the visual system for autonomous flying agent. The core elements of the vision system which were designed and implemented in the earlier stage of the project are brought together. The second aim is to show capabilities of a simulation environment designed and developed by the authors in order to enable testing of the vision systems (dedicated for Unmanned Aerial Vehicles) in the artificial environment. The first section of the paper introduces the testing (simulation) environment for MavLink-protocol-based autonomous flying robots. Next, the core elements of a vision system, designed for Unmanned Aerial Vehicle (UAV), are discussed. This includes pre-processing and vectorization algorithms, object recognition methods and fast three-dimensional model construction. The third part introduces a set of algorithms for robot navigation, solely based on vision and altitude sensor and compass. The paper concludes with the description of the tests and presentation of results where designed simulator was applied to show mentioned vision system elements operating together to execute complex task.

关键词： Robot sensing systems Testing Protocols algorithm design and analysis Navigation

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A Generic Framework for Interesting Subspace Cluster Detection in Multi-attributed Networks 17

A Generic Framework for Interesting Subspace Cluster Detecti...

引用

17th IEEE International Conference on Data Mining (ICDMW)

作者： Chen, Feng Zhou, Baojian Alim, Adil Zhao, Liang SUNY Albany Dept Comp Sci Albany NY 12222 USA George Mason Univ Dept Informat Sci & Technol Fairfax VA 22030 USA

ISBN: (纸本)9781538638354

Detection of interesting (e.g., coherent or anomalous) clusters has been studied extensively on plain or univariate networks, with various applications. Recently, algorithms have been extended to networks with multiple attributes for each node in the real-world. In a multi-attributed network, often, a cluster of nodes is only interesting for a subset (subspace) of attributes, and this type of clusters is called subspace clusters. However, in the current literature, few methods are capable of detecting subspace clusters, which involves concurrent feature selection and network cluster detection. These relevant methods are mostly heuristic-driven and customized for specific application scenarios. In this work, we present a generic and theoretical framework for detection of interesting subspace clusters in large multi-attributed networks. Specifically, we propose a subspace graph-structured matching pursuit algorithm, namely, SG-Pursuit, to address a broad class of such problems for different score functions (e.g., coherence or anomalous functions) and topology constraints (e.g., connected subgraphs and dense subgraphs). We prove that our algorithm 1) runs in nearly-linear time on the network size and the total number of attributes and 2) enjoys rigorous guarantees (geometrical convergence rate and tight error bound) analogous to those of the state-of-the-art algorithms for sparse feature selection problems and subgraph detection problems. As a case study, we specialize SG-Pursuit to optimize a number of well-known score functions for two typical tasks, including detection of coherent dense and anomalous connected subspace clusters in real-world networks. Empirical evidence demonstrates that our proposed generic algorithm SG-Pursuit is superior over state-of-the-art methods that are designed specifically for these two tasks.

关键词： Clustering algorithms Feature extraction Matching pursuit algorithms algorithm design and analysis Surveillance Social network services

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Boosting Feature Based Classifiers for Writer Identification 1

Boosting Feature Based Classifiers for Writer Identification

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1st IEEE International Workshop on Arabic Script analysis and Recognition (ASAR)

作者： Saabni, Raid Tel Aviv Yaffo Acad Coll Triangle R&D Ctr Comp Sci Dept Kafr Qarea Israel

ISBN: (纸本)9781509066285

The identification of a writer of a handwriting image is very useful for applications in forensic and historic document analysis. Writer identification methods retrieve the closest image within a list of samples of different writers to a query sample. In automatic writer verification the system takes an automatic decision if two handwriting images were written by the same person. In recent years, several effective and powerful features were designed to capture and characterize writer individuality and been used in automatic writer identification and verification. A wide variety of classifiers were presented to work with such features presenting impressive results. Mostly, these classifiers assumed that all errors have the same cost and based on specific features set. In this paper, we analyze and improve some of these features and combine them by using boosting methodology which is error cost sensitive to instigate better classifiers. Results on the ICDAR2015 competition data set with KHATTT and ICDAR2011 competition databases, prove that the presented approach improves the accuracy.

关键词： Feature extraction Histograms Boosting Shape Distance measurement algorithm design and analysis

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Anomaly detection of CAN bus messages through analysis of ID sequences 28

Anomaly detection of CAN bus messages through analysis of ID...

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28th IEEE Intelligent Vehicles Symposium (IV)

作者： Marchetti, Mirco Stabili, Dario Univ Modena & Reggio Emilia Dept Engn Enzo Ferrari I-41125 Modena Italy

ISBN: (纸本)9781509048045

This paper proposes a novel intrusion detection algorithm that aims to identify malicious CAN messages injected by attackers in the CAN bus of modern vehicles. The proposed algorithm identifies anomalies in the sequence of messages that flow in the CAN bus and is characterized by small memory and computational footprints, that make it applicable to current ECUs. Its detection performance are demonstrated through experiments carried out on real CAN traffic gathered from an unmodified licensed vehicle.

关键词： Training Memory management algorithm design and analysis Detection algorithms Arrays Intrusion detection

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A recommendation algorithm based on Collaborative Filtering Technology in distance learning 2

A recommendation algorithm based on Collaborative Filtering ...

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2017 IEEE 第2届先进信息技术,电子与自动化控制国际会议(IAEAC 2017)

作者： Ji-chun Zhao Lei Chen Jian xin Guo Beijing Academy of Agriculture and Forestry Sciences The Research Center of Beijing Engineering Technology for Rural Remote Information Services

Online learning resources growth speed is in geometric series with the rapid development of computer and communication technology. Users in distance learning and training process encounter the problem

ISBN: (纸本)9781467389808

关键词： Collaboration Filtering Computer aided instruction algorithm design and analysis Computational modeling Prediction algorithms

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Development of Computer Vision algorithm towards Assessment of Suturing Skill 4

Development of Computer Vision Algorithm towards Assessment ...

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4th IEEE EMBS International Conference on Biomedical and Health Informatics (BHI)

作者： Kil, Irfan Jagannathan, Anand Singapogu, Ravikiran B. Groff, Richard E. Clemson Univ Dept Elect & Comp Engn Clemson SC 29634 USA Clemson Univ Dept Bioengn Clemson SC 29634 USA

ISBN: (纸本)9781509041794

In this paper, we present a computer vision algorithm to extract key information pertinent to assessing surgical suturing. This algorithm uses an instrumented platform designed to quantify suturing skill. As subjects performed suturing on the platform, the vision algorithm computes the time and the location of suture needle's entry and exit, stitch length, needle trace, and hesitation time, which were identified as potential metrics to assess suturing skill. Preliminary experimental data from a study with 14 subjects with minimal suturing experience are presented. The results demonstrate that the algorithm is feasible for use in quantifying suturing expertise.

关键词： Needles Measurement Surgery Yarn algorithm design and analysis Computer vision Data mining

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A Compact Index for Order-Preserving Pattern Matching

A Compact Index for Order-Preserving Pattern Matching

引用

Data Compression Conference (DCC)

作者： Decaroli, Gianni Gagie, Travis Manzini, Giovanni Univ Piemonte Orientale Comp Sci Inst Alessandria Italy Diego Port Univ Santiago Chile CEBIB Santiago Chile CNR CNR IIT Pisa Italy

ISBN: (纸本)9781509067213

Order-preserving pattern matching was first studied surprisingly recently but has already attracted much attention. For this problem we propose a space-efficient index that works well in practice despite its lack of good worst-case time bounds. Our solution is based on the new approach of decomposing the indexed sequence into an order component, containing ordering information, and ad component, containing information on the absolute values. Experiments show that this approach is viable and it is the first one offering simultaneously small space usage and fast retrieval.

关键词： Indexes Pattern matching algorithm design and analysis Data mining Complexity theory Windows

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Showpiece: iSnap Demonstration

Showpiece: iSnap Demonstration

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IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)

作者： Price, Thomas W. Barnes, Tiffany North Carolina State Univ Raleigh NC 27606 USA

ISBN: (纸本)9781538604434

This showpiece will present iSnap, an extension of the block-based, novice programming environment Snap!, which supports struggling students by providing on-demand hints and feedback that help them complete programming assignments. iSnap extends the existing syntactic scaffolding offered by block-based programming to additionally support the implementation of programming tasks. Research on iSnap has explored questions of how visual programming environments can better support learners, the impact of this support, and how learners seek and use computer-based help. The showpiece will consist of an interactive demonstration of iSnap, including the user interface experienced by students and the data-driven algorithm used to automatically generate the programming feedback.

关键词： Programming environments Visualization Programming profession Computers algorithm design and analysis Electronic mail

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