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Scalable Deep Compressive Sensing
Deep learning has been used to image compressive sensing (CS) for enhanc...
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FPGA-based Hyrbid Memory Emulation System
Hybrid memory systems, comprised of emerging non-volatile memory (NVM) a...
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Simultaneous Consensus Maximization and Model Fitting
Maximum consensus (MC) robust fitting is a fundamental problem in low-le...
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AMP-Net: Denoising based Deep Unfolding for Compressive Image Sensing
Most compressive sensing (CS) reconstruction methods can be divided into...
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Hardware Memory Management for Future Mobile Hybrid Memory Systems
The current mobile applications have rapidly growing memory footprints, ...
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Blind Image Deblurring Using Patch-Wise Minimal Pixels Regularization
Blind image deblurring is a long standing challenging problem in image p...
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Robust Precoding Design for Coarsely Quantized MU-MIMO Under Channel Uncertainties
Recently, multi-user multiple input multiple output (MU-MIMO) systems wi...
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Matrix Completion via Nonconvex Regularization: Convergence of the Proximal Gradient Algorithm
Matrix completion has attracted much interest in the past decade in mach...
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Nonconvex Regularization Based Sparse and Low-Rank Recovery in Signal Processing, Statistics, and Machine Learning
In the past decade, sparse and low-rank recovery have drawn much attenti...
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Efficient Outlier Removal for Large Scale Global Structure-from-Motion
This work addresses the outlier removal problem in large-scale global st...
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Benefit of Joint DOA and Delay Estimation with Application to Indoor Localization in WiFi and 5G
Accurate indoor localization has long been a challenging problem due to ...
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Joint DOA and Delay Estimation for 3D Indoor Localization in Next Generation WiFi and 5G
This paper address the joint direction-of-arrival (DOA) and time delay (...
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Positive Definite Estimation of Large Covariance Matrix Using Generalized Nonconvex Penalties
This work addresses the issue of large covariance matrix estimation in h...
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