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An Adaptive robust Online Method for AUC Maximization

IEEE ACCESS 2018年 6卷 52004-52013页

作者： Cheng, Fan Zhang, Xia Zhang, Chuang Qiu, Jianfeng Zhang, Lei Anhui Univ Key Lab Intelligent Comp & Signal Proc Minist Educ Hefei 230039 Anhui Peoples R China Anhui Univ Sch Comp Sci & Technol Hefei 230039 Anhui Peoples R China

Recently, increasing attention has been focused on the problem of online AUC maximization, and a great deal of efficient algorithms has been proposed. In spite of the promising performance of those online algorithms, however, most of them are sensitive to the outliers, which make them unsuitable for the applications with noisy data. To tackle the issue, in this paper, an adaptive robust method for online AUC maximization, termed AROAM is suggested. Specifically, a ramp loss based objective function oriented to AUC metric is firstly defined in AROAM, which has the strong ability of suppressing the influence of outliers. Then, concave-convex procedure is adopted for the convex approximation of the objective function. Finally, to further improve the performance of AROAM, an adaptive learning rate strategy is developed in each iteration, which can update the classifier effectively. Empirical studies on the benchmark data sets demonstrate the superiority of the proposed method in comparison with the state-of-the-arts.

关键词： AUC maximization algorithm online learning ramp loss robust algorithm adaptive learning rate

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robust Efficient Broadband Antenna Array Pattern Synthesis Techniques

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IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION 2014年第9期62卷 4537-4546页

作者： Hossain, M. S. Milford, G. N. Reed, M. C. Godara, L. C. Univ New S Wales Sch Engn & Informat Technol Canberra ACT 2600 Australia

This paper presents efficient robust broadband antenna array pattern synthesis techniques with interference cancellation capabilities. The synthesis techniques are able to place multiple broad nulls and isolated point nulls at regions of interest for interference cancellation. The new synthesis algorithms result in improved performance broadband antenna array processors. The presented synthesis techniques are computationally more efficient than the existing synthesis techniques. The paper includes numerical simulations that demonstrate the performance of the new techniques compared to existing methods.

关键词： Broadband array processor broad null pattern synthesis techniques robust algorithm smart antennas

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robust active noise control: An information theoretic learning approach

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APPLIED ACOUSTICS 2017年第PartA期117卷 180-184页

作者： Kurian, Nikhil Cherian Patel, Kashyap George, Nithin V. Indian Inst Technol Gandhinagar Dept Elect Engn Ahmadabad 382355 Gujarat India

Nonlinear active noise control (ANC) systems, which employ a nonlinear filter as the adaptive controller is not robust when the primary noise to be mitigated has a non-Gaussian distribution. The algorithm which updates the weights of the controller may even diverge for some higher magnitude primary noise signals. With an objective to improve the robustness of nonlinear ANC systems, a correntropy based nonlinear ANC system is developed in this paper. The proposed ANC scheme uses an information theoretic learning approach and has been shown to provide robust noise mitigation even for non-Gaussian primary noise signals. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Active noise control Adaptive filter Information theory Correntropy robust algorithm

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On a robust Approach to Search for Cluster Centers

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AUTOMATION AND REMOTE CONTROL 2021年第10期82卷 1742-1751页

作者： Shibzukhov, Z. M. Moscow Pedag State Univ Inst Math & Comp Sci Moscow 119991 Russia Moscow Inst Phys & Technol Dolgoprudnyi 141701 Moscow Oblast Russia

We propose a new approach to the construction of k-means clustering algorithms in which the Mahalanobis distance is used instead of the Euclidean distance. The approach is based on minimizing differentiable estimates of the mean insensitive to outliers. Illustrative examples convincingly show that the proposed algorithm is highly likely to be robust with respect to a large amount of outliers in the data.

关键词： cluster center robust mean Mahalanobis distance iterative reweighting robust algorithm

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Implementation of a robust complex extended Kalman filter with LabVIEW for detection in a distorted signal

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ARTIFICIAL LIFE AND ROBOTICS 2010年第4期15卷 473-477页

作者： Lin, Wen-Bin Chiang, Huann-Keng Shih, Kuang-Rong Chen, Chien-An Natl Yunlin Univ Sci & Technol Grad Sch Engn Sci & Technol Yunlin Taiwan Natl Yunlin Univ Sci & Technol Dept Elect Engn Yunlin 640 Taiwan Natl Formosa Univ Dept Elect Engn Yunlin Taiwan Automot Res & Testing Ctr Elect Vehicle & Syst Verificat Grp R&D Div Changhua Taiwan

This article proposes the PC-based LabVIEW as the software to develop the algorithm of the robust complex extended Kalman filter (RCEKF) to detect the parameters of the voltage signal in power systems. The hardware used is a sample-and-hold card and a data acquisition (DAQ) card to extract the data from an outside system to the PC, and the program will compute the amplitude, frequency, and phase of the voltage signal with RCEKF. To validate the performance of RCEKF, the voltage signal from a function generator was applied to check the feasibility of the algorithm. This application was also used in the Taiwan Power Company (TPC) secondary substation in Sijhou, Taiwan.

关键词： Complex Kalman filter robust algorithm Voltage distorted signal LabVIEW

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Minimizing robust Estimates of Sums of Parameterized Functions

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Journal of Mathematical Sciences (United States) 2022年第2期260卷 249-264页

作者： Shibzukhov, Z.M. Institute of Applied Mathematics and Automation of the Kabardino-Balkar Scientific Center of the Russian Academy of Sciences Nalchik Russian Federation

The author considers the robust approach to constructing machine learning algorithms based on minimizing robust finite sums of parameterized functions. This algorithm is based on finite robust differentiable aggregation summation functions, which are stable with respect to outliers. © 2022, Springer Science+Business Media, LLC, part of Springer Nature.

关键词： 68T05 averaging aggregation function iterative reweighing neural network robust algorithm

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robust Uniform Concentric Circular Array Beamforming in the Existence of Look Direction Disparity 2

Robust Uniform Concentric Circular Array Beamforming in the ...

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2nd International Conference on Electrical, Computer & Telecommunication Engineering (ICECTE)

作者： Reza, M. F. Hossain, M. S. Hossein, M. T. Rashid, M. M. Rajshahi Univ Engn & Technol RUET Dept Elect & Elect Engn Rajshahi 6204 Bangladesh

ISBN: (纸本)9781509057856

The concentric circular array with robust algorithm is addressed in this paper. A uniform concentric circular array antenna (CCAA) geometry is targeted due to its symmetrical configuration which enables the phased array antenna to scan azimuthally with minimal changes in its beam width and sidelobe levels. This paper first compares the performances of CCAA configuration with existing uniform circular arrays (UCA) to validate the suitability of the presented beamformer. Then the performance of CCAA based optimal beamformer is compared with delay-and-sum beamformer in the presence of interfering signals. The performance of optimal CCAA processor is reduced if signal of interest is deviate from the look direction. This paper also presents a diagonal loading technique to make the system robust for resolving the degradation problem and compare the performance with existing beamforming technique. MATLAB software is used to analyze the performance of proposed CCAA processor.

关键词： Beamforming Optimal beamforming Delay-and-Sum beamformer Diagonal Loading robust algorithm

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robust Sybil Attack Detection Mechanism For Social Networks- A Survey 3

Robust Sybil Attack Detection Mechanism For Social Networks-...

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3rd International Conference on Advanced Computing and Communication Systems (ICACCS)

作者： Valarmathi, M. L. Meenakowshalya, A. Bharathi, A. Govt Coll Technol Comp Sci & Engn Coimbatore Tamil Nadu India

ISBN: (纸本)9781467392068

Now a day's Recommender Systems (RS) have become predominant in Internet of Things (IoT), Online Social Networks (OSN) and Social Internet of Things (SloT). Sybil attack is an attack where malicious users suppress opinions of honest users by creating fake identities called Sybils. Sybil attacks are prevalent in wireless sensor networks, online social networks, Peer to Peer networks and mobile networks. In this paper survey various types of Sybil attacks which are based on behavior of attacker. This paper also surveys different types of current Sybil defense protocols like SybilGuard, SybilLimit, SybilDefender, SybilInfer, SybilShield, and SyMon to defend against the Sybil attack.

关键词： Sybil attack Social network Recommender System robust algorithm

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robust Nonrigid Point Set Registration using Graph-Laplacian Regularization 15

Robust Nonrigid Point Set Registration using Graph-Laplacian...

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IEEE Winter Conference on Applications of Computer Vision (WACV 2015)

作者： Panaganti, Varun Aravind, R. Indian Inst Technol Madras Dept Elect Engn Madras Tamil Nadu India

ISBN: (纸本)9781479966837

We present a robust algorithm that registers one point set to another for nonrigid case. We formulate the problem as a Gaussian mixture model (GMM) density estimation by considering one of the point sets as the GMM centroids and the other as the data points generated by GMM. We displace the centroids and make them register to the data by maximizing the likelihood. To facilitate the process, we introduce a set of weights which provide the proximity information among pairs of points of both point sets and iteratively update the displacement and weights in alternating steps. We propose a priority based combination to update the proximity weights, which leverages the richness of Shape Context (SC). In the displacement updation step, we propose a graph-Laplacian regularization which helps in preserving the intrinsic geometry of the point set to be displaced. We also introduce a fast algorithm that reduces the computation complexity significantly. We apply our method on publicly available datasets. Our results validate the robustness of our approach by outperforming current state-of-the-art methods.

关键词： Gaussian processes graph theory image registration maximum likelihood estimation mixture models GMM centroids GMM density estimation Gaussian mixture model SC computation complexity data points displacement updation step graph-Laplacian regularization intrinsic geometry likelihood maximization priority based combination proximity information proximity weights robust algorithm robust nonrigid point set registration shape context Context Kernel Noise Noise measurement robustness Shape Vectors Noise measurement Set of points Gaussian processes maximum likelihood estimation image registration Graph theory Mixture models Scandium Gm(m) Noise robustness nonrigidity Kernel Centroid

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robust Estimation of Target Reflection Intensity in Remote Sensing Application

Robust Estimation of Target Reflection Intensity in Remote S...

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IEEE International Conference on Electronics, Communications and Control (ICECC)

作者： Jin, Ming Li, Youming Ningbo Univ Coll Informat Sci & Engn Ningbo 315211 Zhejiang Peoples R China

ISBN: (纸本)9781457703218

A robust algorithm for estimating target reflection intensity based on multiple-input multiple-output (MIMO) radar is presented. The algorithm exploits the characteristic of MIMO radar signal model to estimate the reflection intensity. Unlike most robust algorithms such as robust Capon Beamformer (RCB), our method requires no predetermined mismatch range between the actual and normal steering vectors. In addition, the proposed method can be applied to both monostatic and bistatic MIMO radars.

关键词： MIMO radars reflection intensity estimation robust algorithm

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