24 citations · 87 across the 18 of their papers we have counts for
4 papers · 1 filter
Simpler Gradient Methods for Blind Super-Resolution with Lower Iteration Complexity
Jinsheng Li, Wei Cui, Xu Zhang
We study the problem of blind super-resolution, which can be formulated as a low-rank matrix recovery problem via vectorized Hankel lift (VHL). The previous gradient descent method…
Multi-Agent Continuous Control with Generative Flow Networks
Shuang Luo, Yinchuan Li, Shunyu Liu +3
Generative Flow Networks (GFlowNets) aim to generate diverse trajectories from a distribution in which the final states of the trajectories are proportional to the reward, serving…
Fast networked data selection via distributed smoothed quantile estimation
Xu Zhang, Marcos M. Vasconcelos
Collecting the most informative data from a large dataset distributed over a network is a fundamental problem in many fields, including control, signal processing and machine learn…
Projected Gradient Descent for Spectral Compressed Sensing via Symmetric Hankel Factorization
Jinsheng Li, Wei Cui, Xu Zhang
Current spectral compressed sensing methods via Hankel matrix completion employ symmetric factorization to demonstrate the low-rank property of the Hankel matrix. However, previous…