Yonina C. Eldar

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Technion ∙ Weizmann Institute of Science

Professor of Electrical Engineering at Technion - Israel Institute of Technology, Adjunt Professor at Duke University

Algorithm Unrolling: Interpretable, Efficient Deep Learning for Signal and Image Processing

Deep neural networks provide unprecedented performance gains in many rea...
12/22/2019 ∙ by Vishal Monga, et al. ∙ 57 ∙ share

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Semi-supervised Learning in Network-Structured Data via Total Variation Minimization

We propose and analyze a method for semi-supervised learning from partia...
01/28/2019 ∙ by Alexander Jung, et al. ∙ 18 ∙ share

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Fast Deep Learning for Automatic Modulation Classification

In this work, we investigate the feasibility and effectiveness of employ...
01/16/2019 ∙ by Sharan Ramjee, et al. ∙ 18 ∙ share

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An Algorithm Unrolling Approach to Deep Blind Image Deblurring

Blind image deblurring remains a topic of enduring interest. Learning ba...
02/09/2019 ∙ by Yuelong Li, et al. ∙ 10 ∙ share

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Deep Unfolded Robust PCA with Application to Clutter Suppression in Ultrasound

Contrast enhanced ultrasound is a radiation-free imaging modality which ...
11/20/2018 ∙ by Oren Solomon, et al. ∙ 4 ∙ share

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Coupled Dictionary Learning for Multi-contrast MRI Reconstruction

Medical imaging tasks often involve multiple contrasts, such as T1- and ...
06/26/2018 ∙ by Pingfan Song, et al. ∙ 2 ∙ share

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Tradeoffs between Convergence Speed and Reconstruction Accuracy in Inverse Problems

Solving inverse problems with iterative algorithms is popular, especiall...
05/30/2016 ∙ by Raja Giryes, et al. ∙ 0 ∙ share

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Solving Systems of Random Quadratic Equations via Truncated Amplitude Flow

This paper presents a new algorithm, termed truncated amplitude flow (TA...
05/26/2016 ∙ by Gang Wang, et al. ∙ 0 ∙ share

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DOLPHIn - Dictionary Learning for Phase Retrieval

We propose a new algorithm to learn a dictionary for reconstructing and ...
02/06/2016 ∙ by Andreas M. Tillmann, et al. ∙ 0 ∙ share

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Sparse Nonlinear Regression: Parameter Estimation and Asymptotic Inference

We study parameter estimation and asymptotic inference for sparse nonlin...
11/14/2015 ∙ by Zhuoran Yang, et al. ∙ 0 ∙ share

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Performance Limits of Dictionary Learning for Sparse Coding

We consider the problem of dictionary learning under the assumption that...
02/17/2014 ∙ by Alexander Jung, et al. ∙ 0 ∙ share

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Compressive Shift Retrieval

The classical shift retrieval problem considers two signals in vector fo...
03/20/2013 ∙ by Henrik Ohlsson, et al. ∙ 0 ∙ share

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Semi-Supervised Single- and Multi-Domain Regression with Multi-Domain Training

We address the problems of multi-domain and single-domain regression bas...
03/20/2012 ∙ by Tomer Michaeli, et al. ∙ 0 ∙ share

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Compressed sensing for longitudinal MRI: An adaptive-weighted approach

Purpose: Repeated brain MRI scans are performed in many clinical scenari...
07/10/2014 ∙ by Lior Weizman, et al. ∙ 0 ∙ share

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Compressed Beamforming in Ultrasound Imaging

Emerging sonography techniques often require increasing the number of tr...
02/09/2012 ∙ by Noam Wagner, et al. ∙ 0 ∙ share

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The Projected GSURE for Automatic Parameter Tuning in Iterative Shrinkage Methods

Linear inverse problems are very common in signal and image processing. ...
03/21/2010 ∙ by Raja Giryes, et al. ∙ 0 ∙ share

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Hybrid Analog-Digital Beamforming for Massive MIMO Systems

In massive MIMO systems, hybrid beamforming is an essential technique fo...
12/10/2017 ∙ by Shahar Stein Ioushua, et al. ∙ 0 ∙ share

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On the Sample Complexity of Multichannel Frequency Estimation via Convex Optimization

The use of multichannel data in estimating a set of frequencies is commo...
12/15/2017 ∙ by Zai Yang, et al. ∙ 0 ∙ share

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Pilot Contamination Mitigation with Reduced RF Chains

Massive multiple-input multiple-output (MIMO) communication is a promisi...
01/16/2018 ∙ by Shahar S. Ioushua, et al. ∙ 0 ∙ share

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Analog-to-Digital Compression: A New Paradigm for Converting Signals to Bits

Processing, storing and communicating information that originates as an ...
01/20/2018 ∙ by Alon Kipnis, et al. ∙ 0 ∙ share

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On the Spectral Efficiency of Noncooperative Uplink Massive MIMO Systems

Massive multiple-input multiple-output (MIMO) systems have been drawing ...
02/09/2018 ∙ by Nir Shlezinger, et al. ∙ 0 ∙ share

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Cognitive Radar Antenna Selection via Deep Learning

Direction of arrival (DoA) estimation of targets improves with the numbe...
02/27/2018 ∙ by Ahmet M. Elbir, et al. ∙ 0 ∙ share

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RAPToR: A Resampling Algorithm for Pseudo-Polar based Tomographic Reconstruction

We propose a stable and fast reconstruction technique for parallel-beam ...
08/17/2017 ∙ by Shahar Tsiper, et al. ∙ 0 ∙ share

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Sub-Nyquist Radar: Principles and Prototypes

In the past few years, new approaches to radar signal processing have be...
03/05/2018 ∙ by Kumar Vijay Mishra, et al. ∙ 0 ∙ share

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Super-resolution Ultrasound Localization Microscopy through Deep Learning

Ultrasound localization microscopy has enabled super-resolution vascular...
04/20/2018 ∙ by Ruud J. G. van Sloun, et al. ∙ 0 ∙ share

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The Global Optimization Geometry of Shallow Linear Neural Networks

We examine the squared error loss landscape of shallow linear neural net...
05/13/2018 ∙ by Zhihui Zhu, et al. ∙ 0 ∙ share

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Sparse Convolutional Beamforming for Ultrasound Imaging

The standard technique used by commercial medical ultrasound systems to ...
05/14/2018 ∙ by Regev Cohen, et al. ∙ 0 ∙ share

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Subspace Estimation from Incomplete Observations: A High-Dimensional Analysis

We present a high-dimensional analysis of three popular algorithms, name...
05/17/2018 ∙ by Chuang Wang, et al. ∙ 0 ∙ share

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Analog to Digital Cognitive Radio: Sampling, Detection and Hardware

The proliferation of wireless communications has recently created a bott...
08/17/2017 ∙ by Deborah Cohen, et al. ∙ 0 ∙ share

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Sampling and Super-resolution of Sparse Signals Beyond the Fourier Domain

Recovering a sparse signal from its low-pass projections in the Fourier ...
06/05/2018 ∙ by Ayush Bhandari, et al. ∙ 0 ∙ share

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On MIMO Channel Capacity with Output Quantization Constraints

The capacity of a Multiple-Input Multiple-Output (MIMO) channel in which...
06/05/2018 ∙ by Abbas Khalili, et al. ∙ 0 ∙ share

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iMAP Beamforming for High Quality High Frame Rate Imaging

We present a statistical interpretation of beamforming to overcome limit...
06/09/2018 ∙ by Tanya Chernyakova, et al. ∙ 0 ∙ share

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Analysis of Frequency Agile Radar via Compressed Sensing

Frequency agile radar (FAR) is known to have excellent electronic counte...
08/28/2018 ∙ by Tianyao Huang, et al. ∙ 0 ∙ share

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A Cognitive Sub-Nyquist MIMO Radar Prototype

We present a prototype that demonstrates the principle of a colocated, f...
07/23/2018 ∙ by Kumar Vijay Mishra, et al. ∙ 0 ∙ share

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Hardware-Limited Task-Based Quantization

Quantization plays a critical role in digital signal processing systems....
07/22/2018 ∙ by Nir Shlezinger, et al. ∙ 0 ∙ share

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Sub-Nyquist Radar Systems: Temporal, Spectral and Spatial Compression

Conventional radar transmits electromagnetic waves towards the targets o...
07/30/2018 ∙ by Deborah Cohen, et al. ∙ 0 ∙ share

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Blind Phaseless Short-Time Fourier Transform Recovery

The problem of recovering a pair of signals from their blind phaseless s...
08/22/2018 ∙ by Tamir Bendory, et al. ∙ 0 ∙ share

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Convolutional Phase Retrieval via Gradient Descent

We study the convolutional phase retrieval problem, which considers reco...
12/03/2017 ∙ by Qing Qu, et al. ∙ 0 ∙ share

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Functional Nonlinear Sparse Models

Signal processing in inherently continuous and often nonlinear applicati...
11/01/2018 ∙ by Luiz F. O. Chamon, et al. ∙ 0 ∙ share

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Deep Signal Recovery with One-Bit Quantization

Machine learning, and more specifically deep learning, have shown remark...
11/30/2018 ∙ by Shahin Khobahi, et al. ∙ 0 ∙ share

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Dynamic Metasurface Antennas for Uplink Massive MIMO Systems

Massive multiple-input multiple-output (MIMO) communications are the foc...
01/05/2019 ∙ by Nir Shlezinger, et al. ∙ 0 ∙ share

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On Multiterminal Communication over MIMO Channels with One-bit ADCs at the Receivers

The fundamental limits of communication over multiple-input multiple-out...
01/30/2019 ∙ by Abbas Khalili, et al. ∙ 0 ∙ share

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An Algorithm Unrolling Approach to Deep Image Deblurring

While neural networks have achieved vastly enhanced performance over tra...
02/09/2019 ∙ by Yuelong Li, et al. ∙ 0 ∙ share

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Tradeoff Between Delay and High SNR Capacity in Quantized MIMO Systems

Analog-to-digital converters (ADCs) are a major contributor to the power...
01/28/2019 ∙ by Abbas Khalili, et al. ∙ 0 ∙ share

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The Capacity of Memoryless Channels with Sampled Cyclostationary Gaussian Noise

Non-orthogonal communications play an important role in future communica...
02/24/2019 ∙ by Nir Shlezinger, et al. ∙ 0 ∙ share

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Sample Efficient Toeplitz Covariance Estimation

We study the query complexity of estimating the covariance matrix T of a...
05/14/2019 ∙ by Yonina C. Eldar, et al. ∙ 0 ∙ share

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Coordinated Nonorthogonal Pilot Design for Massive MIMO

Pilot contamination caused by the nonorthogonality of pilots is a main l...
04/21/2019 ∙ by Kaiming Shen, et al. ∙ 0 ∙ share

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Deep Learning for Interference Identification: Band, Training SNR, and Sample Selection

We study the problem of interference source identification, through the ...
05/16/2019 ∙ by Xiwen Zhang, et al. ∙ 0 ∙ share

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ViterbiNet: A Deep Learning Based Viterbi Algorithm for Symbol Detection

Symbol detection plays an important role in the implementation of digita...
05/26/2019 ∙ by Nir Shlezinger, et al. ∙ 0 ∙ share

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A Block Sparsity Based Estimator for mmWave Massive MIMO Channels with Beam Squint

Multiple-input multiple-output (MIMO) millimeter wave (mmWave) communica...
04/28/2019 ∙ by Mingjin Wang, et al. ∙ 0 ∙ share

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Yonina C. Eldar

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