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检索条件"主题词=Optimization algorithms"

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ECC: Platform-Independent Energy-Constrained Deep Neural Network Compression via a Bilinear Regression Model

ECC: Platform-Independent Energy-Constrained Deep Neural Net...

引用

IEEE/CVF Conference on Computer Vision and Pattern Recognition

作者： Haichuan Yang Yuhao Zhu Ji Liu University of Rochester Kwai Seattle AI Lab

ISBN: (纸本)9781728132945

Many DNN-enabled vision applications constantly operate under severe energy constraints such as unmanned aerial vehicles, Augmented Reality headsets, and smart-phones. Designing DNNs that can meet a stringent energy budget is becoming increasingly important. This paper proposes ECC, a framework that compresses DNNs to meet a given energy constraint while minimizing accuracy loss. The key idea of ECC is to model the DNN energy consumption via a novel bilinear regression function. The energy estimate model allows us to formulate DNN compression as a constrained optimization that minimizes the DNN loss function over the energy constraint. The optimization problem, however, has nontrivial constraints. Therefore, existing deep learning solvers do not apply directly. We propose an optimization algorithm that combines the essence of the Alternating Direction Method of Multipliers (ADMM) framework with gradient-based learning algorithms. The algorithm decomposes the original constrained optimization into several subproblems that are solved iteratively and efficiently. ECC is also portable across different hardware platforms without requiring hardware knowledge. Experiments show that ECC achieves higher accuracy under the same or lower energy budget compared to state-of-the-art resource-constrained DNN compression techniques.

关键词： Error correction codes Elliptic curve cryptography EMERGENCY CONTROL CENTERS Hardware Platform Constrained optimization Energy budget optimization algorithms bilinearity platform-independent Energy sources Essences simple regression (model)

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Compressive imaging with iterative forward models

Compressive imaging with iterative forward models

引用

IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Hsiou-Yuan Liu Ulugbek S. Kamilov Dehong Liu Hassan Mansour Petros T. Boufounos Department of Electrical Engineering & Computer Sciences University of California Berkeley 94720 USA Mitsubishi Electric Research Laboratories (MERL) Cambridge MA 02139 USA

ISBN: (纸本)9781509041183

We propose a new compressive imaging method for reconstructing 2D or 3D objects from their scattered wave-field measurements. Our method relies on a novel, nonlinear measurement model that can account for the multiple scattering phenomenon, which makes the method preferable in applications where linear measurement models are inaccurate. We construct the measurement model by expanding the scattered wave-field with an accelerated-gradient method, which is guaranteed to converge and is suitable for large-scale problems. We provide explicit formulas for computing the gradient of our measurement model with respect to the unknown image, which enables image formation with a sparsity-driven numerical optimization algorithm. We validate the method both analytically and with numerical simulations.

关键词： Computational imaging inverse scattering sparse reconstruction total variation regularization inverse scattering Scattering optimization algorithms Image formation Imaging Linear measurement Inaccurate Iterative

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Symmetric Upwind Scheme for Discrete Weighted Total Variation

Symmetric Upwind Scheme for Discrete Weighted Total Variatio...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Sonia Tabti Julien Rabin Abderrahim Elmoata Normandie Univ UNICAEN ENSICAEN CNRS GREYC 14000 Caen France

ISBN: (纸本)9781538646595

This paper is devoted to the study of the discrete formulations of the weighted Total Variation (TV) based on upwind schemes that have been proposed for imaging problems in a local setting in [1] and in a non-local setting for graphs and point-clouds in [2]. We focus on two new symmetric formulations based on the I~2 and I~∞ norms respectively and propose a dedicated optimization algorithm to solve convex problems based on such TV penalties. We demonstrate the theoretical and practical interest of such formulations for image processing tasks.

关键词： Weighted Total Variation Upwind scheme image denoising isotropy preservation co-area formula upwind scheme image denoising Area formula CENTROSYMMETRIC image processing task optimization algorithms Television

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Spectral Reconstruction from Dispersive Blur: A Novel Light Efficient Spectral Imager

Spectral Reconstruction from Dispersive Blur: A Novel Light ...

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IEEE/CVF Conference on Computer Vision and Pattern Recognition

作者： Yuanyuan Zhao Xuemei Hu Hui Guo Zhan Ma Tao Yue Xun Cao Nanjing University

ISBN: (纸本)9781728132945

Developing high light efficiency imaging techniques to retrieve high dimensional optical signal is a long-term goal in computational photography. Multispectral imaging, which captures images of different wavelengths and boosting the abilities for revealing scene properties, has developed rapidly in the last few decades. From scanning method to snapshot imaging, the limit of light collection efficiency is kept being pushed which enables wider applications especially under the light-starved scenes. In this work, we propose a novel multispectral imaging technique, that could capture the multispectral images with a high light efficiency. Through investigating the dispersive blur caused by spectral dispersers and introducing the difference of blur (DoB) constraints, we propose a basic theory for capturing multispectral information from a single dispersive-blurred image and an additional spectrum of an arbitrary point in the scene. Based on the theory, we design a prototype system and develop an optimization algorithm to realize snapshot multispectral imaging. The effectiveness of the proposed method is verified on both the synthetic data and real captured images.

关键词： collection efficiency images multispectral imagery Snapshots dispersion optimization algorithms scanning method Light synthetic data imaging instrument

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Performance of Uniaxial Multilayer Cylinders and Spheres Used for Invisible Cloak Realization

Performance of Uniaxial Multilayer Cylinders and Spheres Use...

引用

European Conference on Antennas and Propagation

作者： Branimir Ivsic Tin Komljenovic Zvonimir Sipus University of Zagreb Faculty of Electrical Engineering and Computing Department of Wireless Communications

ISBN: (纸本)9781457702501

The paper presents the analysis of cylindrical and spherical structures used for invisible cloak realization. Different cylindrical and spherical cloak realizations were analyzed in terms of bistatic scattering cross section. In addition, optimization algorithm was connected with the analysis routine to find the constitutive parameters of the cloak that reduce both backscattering and forward scattering. The results show that it is possible to obtain adequate invisibility performance by covering the PEC sphere with only 2 thin anisotropic layers.

关键词： Spheres invisibility performance Spheroidal structure optimization algorithms Cylindrical backscattering Cylinders Cylinders Cross section bistatic scattering forward scattering multilayers swine enteric calicivirus

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Gauss-Newton Observers for Mode and Continuous State Estimation of Nonlinear Switched Systems

Gauss-Newton Observers for Mode and Continuous State Estimat...

引用

Proceedings of the 46th IEEE Conference on Decision and Control, Pages 4135-4592

作者： Rudy Kajdan Didier Aubry Frederic Kratz ENSI de Bourges Laboratoire de Vision et Robotique Bourges France

ISBN: (纸本)9781424414970;1424414970

The purpose of this paper is to design a moving horizon observer for mode and continuous state estimation of nonlinear switched systems. Using the past output measurements and the model equations, mode and continuous state estimation is expressed as an optimization problem which is solved using the Gauss-Newton algorithm. The performances of this method are illustrated on a simulated two-tank system.

关键词： switched systems nonlinear systems estimation optimization algorithms

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Adaptive Maximization of Pointwise Submodular Functions With Budget Constraint 16

Adaptive Maximization of Pointwise Submodular Functions With...

引用

Annual Conference on Neural Information Processing Systems

作者： Nguyen Viet Cuong Huan Xu Department of Engineering University of Cambridge Stewart School of Industrial & Systems Engineering Georgia Institute of Technology

ISBN: (纸本)9781510838819

We study the worst-case adaptive optimization problem with budget constraint that is useful for modeling various practical applications in artificial intelligence and machine learning. We investigate the near-optimality of greedy algorithms for this problem with both modular and non-modular cost functions. In both cases, we prove that two simple greedy algorithms are not near-optimal but the best between them is near-optimal if the utility function satisfies pointwise submodularity and pointwise cost-sensitive submodularity respectively. This implies a combined algorithm that is near-optimal with respect to the optimal algorithm that uses half of the budget. We discuss applications of our theoretical results and also report experiments comparing the greedy algorithms on the active learning problem.

关键词： greedy algorithm Budgets Artificial Intelligence optimization algorithms Modularity

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Robust PCA via Nonconvex Rank Approximation

Robust PCA via Nonconvex Rank Approximation

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IEEE International Conference on Data Mining

作者： Zhao Kang Chong Peng Qiang Cheng Department of Computer Science Southern Illinois University

ISBN: (纸本)9781467395052

Numerous applications in data mining and machine learning require recovering a matrix of minimal rank. Robust principal component analysis (RPCA) is a general framework for handling this kind of problems. Nuclear norm based convex surrogate of the rank function in RPCA is widely investigated. Under certain assumptions, it can recover the underlying true low rank matrix with high probability. However, those assumptions may not hold in real-world applications. Since the nuclear norm approximates the rank by adding all singular values together, which is essentially a l_1-norm of the singular values, the resulting approximation error is not trivial and thus the resulting matrix estimator can be significantly biased. To seek a closer approximation and to alleviate the above-mentioned limitations of the nuclear norm, we propose a nonconvex rank approximation. This approximation to the matrix rank is tighter than the nuclear norm. To solve the associated nonconvex minimization problem, we develop an efficient augmented Lagrange multiplier based optimization algorithm. Experimental results demonstrate that our method outperforms current state-of-the-art algorithms in both accuracy and efficiency.

关键词： Rank of data data mining approximation principal components analysis Approximation error Atomic nuclei matrices optimization algorithms

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CT SLICE RETRIEVAL BY SHAPE ELLIPSES DESCRIPTORS FOR SKULL REPAIRING

CT SLICE RETRIEVAL BY SHAPE ELLIPSES DESCRIPTORS FOR SKULL R...

引用

IEEE International Conference on Image Processing

作者： Marcelo Rudek Osiris Canciglieri Andreas Jahnen Gerson Linck Bichinho Industrial and Systems Engineering Graduate Program - Pontifical Catholic University of Parana PUCPR Brazil. Ressource Centre for HealthCare Technologies (SANTEC) Public Research Centre Henri Tudor Luxembourg. Technology in Healthcare Postgraduate Program - Pontifical Catholic University of Parana PUCPR Brazil.

ISBN: (纸本)9781479923427

This paper addresses the problem of automated prosthesis modelling and manufacturing, whose machining parameters are based on images extracted from different medical databases. The specific case of 3D surface restoration of a defective skull was used as study case. A method based on adjusted ellipses on skull bone curvature performs the symbolic representation of searching parameters. The superellipse concept permits to define geometric parameters to fit an ellipse on each Computed Tomography slice. Those ellipse descriptors can be used as a template for the retrieval of similar images from databases whose parameters match the sampled image. The similarity is measured according to the best fitness values through an optimization algorithm. The slices found by similarity are retrieved from all databases in order to build the 3D model. Experiments show that the proposed method is a promising technique for content based image retrieval.

关键词： Prosthesis Modelling Image Retrieval Ellipse 3D Medical Imaging Ellipse image retrieval Medical imaging content-based image retrieval Skull retrieval Database X-Ray Computed Tomography Three Dimensions Descriptors images geometric parameter optimization algorithms

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Solving Traveling Salesman Problem with Hybrid Estimation of Distribution Algorithm

Solving Traveling Salesman Problem with Hybrid Estimation of...

引用

IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems

作者： Libo Song Chang Liu Jun Zhu Haibo Shi Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9781538604915

A hybrid distribution estimation algorithm for traveling salesman problem is proposed. Firstly, based on the distributed estimation algorithm, a new effective probability model is proposed to solve the traveling salesman problem. Secondly, in order to speed up the optimization of the algorithm to prevent the algorithm falling into the local optimal, the extreme optimization algorithm is combined to form a hybrid distribution estimation algorithm to improve the effectiveness of the algorithm. Then through the public TSPLIB data set, it is proved that the hybrid distribution estimation algorithm is effective, and the algorithm can solve this kind of problem well. Finally, a new idea is proposed to verify the validity of the traveling salesman problem, and the algorithm is tested by the proposed algorithm. The experimental results show that the proposed hybrid distribution estimation algorithm has a good performance in solving the traveling salesman problem.

关键词： Urban areas Estimation Traveling salesman problems optimization Sociology Statistics Encoding travelling salesman problems Sociology algorithms urban area Allocation Algorithm coding optimization algorithms HYBRID Hybrid electric vehicles

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