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Utilization of convex optimization for data fusion-driven sensor management in WSNs.

, , and . IWCMC, page 1224-1229. IEEE, (2015)

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Fast Low-Rank Matrix Estimation for Ill-Conditioned Matrices., and . ISIT, page 371-375. IEEE, (2018)Towards Provable Learning of Polynomial Neural Networks Using Low-Rank Matrix Estimation., and . AISTATS, volume 84 of Proceedings of Machine Learning Research, page 1417-1426. PMLR, (2018)Learning Generative Models of Structured Signals from Their Superposition Using GANs with Application to Denoising and Demixing., , and . CoRR, (2019)Data fusion utilization for optimizing large-scale Wireless Sensor Networks., , and . ICC, page 367-372. IEEE, (2014)Utilization of convex optimization for data fusion-driven sensor management in WSNs., , and . IWCMC, page 1224-1229. IEEE, (2015)Multi-Agent Adversarial Attacks for Multi-Channel Communications., , , and . CoRR, (2022)Perception-Distortion Trade-Off with Restricted Boltzmann Machines., , , , and . ICASSP, page 4022-4026. IEEE, (2020)Unsupervised Demixing of Structured Signals from Their Superposition Using GANs., , and . DGS@ICLR, OpenReview.net, (2019)Fast and Provable Algorithms for Learning Two-Layer Polynomial Neural Networks., and . IEEE Trans. Signal Processing, 67 (13): 3361-3371 (2019)On The Energy Statistics of Feature Maps in Pruning of Neural Networks with Skip-Connections., , , , and . CoRR, (2022)