research
∙
02/25/2023
Average case analysis of Lasso under ultra-sparse conditions
We analyze the performance of the least absolute shrinkage and selection...
share
research
∙
02/02/2023
QCM-SGM+: Improved Quantized Compressed Sensing With Score-Based Generative Models for General Sensing Matrices
In realistic compressed sensing (CS) scenarios, the obtained measurement...
research
∙
11/20/2022
Diffusion Model Based Posterior Sampling for Noisy Linear Inverse Problems
We consider the ubiquitous linear inverse problems with additive Gaussia...
research
∙
11/02/2022
Quantized Compressed Sensing with Score-Based Generative Models
We consider the general problem of recovering a high-dimensional signal ...
research
∙
10/17/2022
A Unitary Transform Based Generalized Approximate Message Passing
We consider the problem of recovering an unknown signal 𝐱∈ℝ^n from gener...
research
∙
02/10/2022
Exact Solutions of a Deep Linear Network
This work finds the exact solutions to a deep linear network with weight...
research
∙
01/30/2022
Stochastic Neural Networks with Infinite Width are Deterministic
This work theoretically studies stochastic neural networks, a main type ...
research
∙
10/16/2021
On Model Selection Consistency of Lasso for High-Dimensional Ising Models on Tree-like Graphs
We consider the problem of high-dimensional Ising model selection using ...
research
∙
02/08/2021
Ising Model Selection Using ℓ_1-Regularized Linear Regression
We theoretically investigate the performance of ℓ_1-regularized linear r...
research
∙
08/19/2020
Structure Learning in Inverse Ising Problems Using ℓ_2-Regularized Linear Estimator
Inferring interaction parameters from observed data is a ubiquitous requ...
research
∙
07/09/2020
Training Restricted Boltzmann Machines with Binary Synapses using the Bayesian Learning Rule
Restricted Boltzmann machines (RBMs) with low-precision synapses are muc...
research
∙
02/25/2020
Training Binary Neural Networks using the Bayesian Learning Rule
Neural networks with binary weights are computation-efficient and hardwa...
research
∙
12/12/2018
Turbo-like Iterative Multi-user Receiver Design for 5G Non-orthogonal Multiple Access
Non-orthogonal multiple access (NoMA) as an efficient way of radio resou...
research
∙
12/12/2018
A Universal Receiver for Uplink NOMA Systems
Given its capability in efficient radio resource sharing, non-orthogonal...
research
∙
11/14/2018
Off-grid Variational Bayesian Inference of Line Spectral Estimation from One-bit Samples
In this paper, the line spectral estimation (LSE) problem is studied fro...
research
∙
10/18/2018
Bilinear Adaptive Generalized Vector Approximate Message Passing
This paper considers the generalized bilinear recovery problem which aim...
research
∙
09/11/2018
Compressive Massive Random Access for Massive Machine-Type Communications (mMTC)
In future wireless networks, one fundamental challenge for massive machi...
research
∙
05/08/2018
Binary Sparse Bayesian Learning Algorithm for One-bit Compressed Sensing
In this letter, a binary sparse Bayesian learning (BSBL) algorithm is pr...
research
∙
12/29/2017
