
Structure Learning in Inverse Ising Problems Using ℓ_2Regularized Linear Estimator
Inferring interaction parameters from observed data is a ubiquitous requ...
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Training Restricted Boltzmann Machines with Binary Synapses using the Bayesian Learning Rule
Restricted Boltzmann machines (RBMs) with lowprecision synapses are muc...
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Training Binary Neural Networks using the Bayesian Learning Rule
Neural networks with binary weights are computationefficient and hardwa...
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Turbolike Iterative Multiuser Receiver Design for 5G Nonorthogonal Multiple Access
Nonorthogonal multiple access (NoMA) as an efficient way of radio resou...
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A Universal Receiver for Uplink NOMA Systems
Given its capability in efficient radio resource sharing, nonorthogonal...
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Offgrid Variational Bayesian Inference of Line Spectral Estimation from Onebit Samples
In this paper, the line spectral estimation (LSE) problem is studied fro...
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Bilinear Adaptive Generalized Vector Approximate Message Passing
This paper considers the generalized bilinear recovery problem which aim...
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Compressive Massive Random Access for Massive MachineType Communications (mMTC)
In future wireless networks, one fundamental challenge for massive machi...
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Binary Sparse Bayesian Learning Algorithm for Onebit Compressed Sensing
In this letter, a binary sparse Bayesian learning (BSBL) algorithm is pr...
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A Unified Bayesian Inference Framework for Generalized Linear Models
In this letter, we present a unified Bayesian inference framework for ge...
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Xiangming Meng
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