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Found 4 papers, 0 papers with code
Provably Robust Score-Based Diffusion Posterior Sampling for Plug-and-Play Image Reconstruction
This work develops an algorithmic framework for employing score-based diffusion models as an expressive data prior in general nonlinear inverse problems.
Provably Accelerating Ill-Conditioned Low-rank Estimation via Scaled Gradient Descent, Even with Overparameterization
Many problems encountered in science and engineering can be formulated as estimating a low-rank object (e. g., matrices and tensors) from incomplete, and possibly corrupted, linear measurements.
The Power of Preconditioning in Overparameterized Low-Rank Matrix Sensing
We propose $\textsf{ScaledGD($\lambda$)}$, a preconditioned gradient descent method to tackle the low-rank matrix sensing problem when the true rank is unknown, and when the matrix is possibly ill-conditioned.
Phase Transitions in Frequency Agile Radar Using Compressed Sensing
FAR has improved anti-jamming performance over traditional pulse-Doppler radars under complex electromagnetic circumstances.
