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05/31/2023
On the Linear Convergence of Policy Gradient under Hadamard Parameterization
The convergence of deterministic policy gradient under the Hadamard para...
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07/15/2022
Approximation Theory of Total Variation Minimization for Data Completion
Total variation (TV) minimization is one of the most important technique...
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09/09/2021
Is Attention Better Than Matrix Decomposition?
As an essential ingredient of modern deep learning, attention mechanism,...
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12/12/2020
Image Restoration: Structured Low Rank Matrix Framework for Piecewise Smooth Functions and Beyond
Recently, mapping a signal/image into a low rank Hankel/Toeplitz matrix ...
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08/12/2020
Vectorized Hankel Lift: A Convex Approach for Blind Super-Resolution of Point Sources
We consider the problem of resolving r point sources from n samples at t...
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11/08/2019
Off-the-Grid Compressed Sensing MRI Reconstruction via Data Driven Tight Frame Regularization
Recently, the finite-rate-of-innovation (FRI) based continuous domain re...
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10/07/2019
Exact matrix completion based on low rank Hankel structure in the Fourier domain
Matrix completion is about recovering a matrix from its partial revealed...
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06/09/2019
Fast Cadzow's Algorithm and a Gradient Variant
The Cadzow's algorithm is a signal denoising and recovery method which w...
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09/27/2018
Towards the optimal construction of a loss function without spurious local minima for solving quadratic equations
The problem of finding a vector x which obeys a set of quadratic equatio...
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09/11/2018
Exploiting the structure effectively and efficiently in low rank matrix recovery
Low rank model arises from a wide range of applications, including machi...
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10/16/2017
