Suchergebnisse - "majorization-minimization algorithm"

Majorization–minimization algorithms for nonsmoothly penalized objective functions von Schifano, Elizabeth D., Strawderman, Robert L., Wells, Martin T.

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Exact minimum rank approximation via Schatten p-norm minimization von Liu, Lu, Huang, Wei, Chen, Di-Rong

“… Recht and Fazel concluded that nuclear norm minimization subject to affine constraints is equivalent to rank minimization under a certain condition in terms of the rank-restricted isometry property …”
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D-optimal sensor selection in the presence of correlated measurement noise von Uciński, Dariusz

“… •A relaxation technique to sensor selection for ordinary least squares is proposed.•The problem is reduced to a sequence of convex optimum experimental design …”
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Secrecy Throughput Maximization for IRS-aided MIMO Wireless Powered Communication Networks von Shi, Weiping, Wu, Qingqing, Xiao, Fu, Shu, Feng, Wang, Jiangzhou

“… ), the information transmit beamforming matrix of users and the phase shifts of IRS in DL/UL, subject to constraints of energy/information transmit power at the hybrid AP/users and that of unit-modulus …”
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Multi-Group Multicasting Using Reconfigurable Intelligent Surfaces: A Deep Learning Approach von Ding, Chunxia, Jin, Weijie, Li, Xiao, Matthaiou, Michail, Yi, Xinping, Jin, Shi

“… This paper considers a downlink multi-group multicast system underpinned by multiple RISs and aims to maximize the sum spectral efficiency subject to an overall transmit power constraint …”
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Hybrid Precoding Design for Subarray-Structure-Enabled mmWave URLLC System von Liu, Zhiren, Shen, Yuan, Qiang, Mengye, Wang, Gang, Wang, Jun-Bo

“… In our system, an achievable rate maximization problem is established by jointly optimizing the analog and digital precoders at the base station, subject to the constraint of the total power …”
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Noisy Depth Maps Fusion for Multiview Stereo Via Matrix Completion von Deng, Yue, Liu, Yebin, Dai, Qionghai, Zhang, Zengke, Wang, Yao

“… Therefore, an intuitive approach to complete the matrix is by minimizing its rank subject to consistency with observed …”
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Training Data Subset Selection for Regression with Controlled Generalization Error von Sivasubramanian, Durga, Iyer, Rishabh, Ramakrishnan, Ganesh, De, Abir

“… trainable parameters and the subset of training data, subject to error bounds on the validation set. We tackle this problem …”
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Robust principal component analysis via re-weighted minimization algorithms von Katselis, Dimitrios, Beck, Carolyn L.

“… Many standard procedures in statistics such as linear regression and principal component analysis (PCA) are inconsistent in high-dimensional settings, where …”
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