1 citations · 1 across the 3 of their papers we have counts for
9 papers
Training Restricted Boltzmann Machines with Binary Synapses using the Bayesian Learning Rule
Xiangming Meng
Restricted Boltzmann machines (RBMs) with low-precision synapses are much appealing with high energy efficiency. However, training RBMs with binary synapses is challenging due to t…
Training Binary Neural Networks using the Bayesian Learning Rule
Xiangming Meng, Roman Bachmann, Mohammad Emtiyaz Khan
Neural networks with binary weights are computation-efficient and hardware-friendly, but their training is challenging because it involves a discrete optimization problem. Surprisi…
Turbo-like Iterative Multi-user Receiver Design for 5G Non-orthogonal Multiple Access
Xiangming Meng, Yiqun Wu, Chao Wang +1
Non-orthogonal multiple access (NoMA) as an efficient way of radio resource sharing has been identified as a promising technology in 5G to help improving system capacity, user conn…
A Universal Receiver for Uplink NOMA Systems
Xiangming Meng, Yiqun Wu, Chao Wang +1
Given its capability in efficient radio resource sharing, non-orthogonal multiple access (NOMA) has been identified as a promising technology in 5G to improve the system capacity,…
Grid-less Variational Bayesian Inference of Line Spectral from Quantized Samples
Jiang Zhu, Qi Zhang, Xiangming Meng
Efficient estimation of line spectral from quantized samples is of significant importance in information theory and signal processing, e.g., channel estimation in energy efficient…
Bilinear Adaptive Generalized Vector Approximate Message Passing
Xiangming Meng, Jiang Zhu
This paper considers the generalized bilinear recovery problem which aims to jointly recover the vector and the matrix from componentwise nonlinear measurem…