1 citations · 1 across the 6 of their papers we have counts for
5 papers
Sparse Recovery for Overcomplete Frames: Sensing Matrices and Recovery Guarantees
Xuemei Chen, Christian Kümmerle, Rongrong Wang
Signal models formed as linear combinations of few atoms from an over-complete dictionary or few frame vectors from a redundant frame have become central to many applications in hi…
Tensor Deli: Tensor Completion for Low CP-Rank Tensors via Random Sampling
Cullen Haselby, Mark Iwen, Santhosh Karnik +1
We propose two provably accurate methods for low CP-rank tensor completion - one using adaptive sampling and one using nonadaptive sampling. Both of our algorithms combine matrix c…
Analysis of Deep Image Prior and Exploiting Self-Guidance for Image Reconstruction
Shijun Liang, Evan Bell, Qing Qu +2
The ability of deep image prior (DIP) to recover high-quality images from incomplete or corrupted measurements has made it popular in inverse problems in image restoration and medi…
PAC-tuning:Fine-tuning Pretrained Language Models with PAC-driven Perturbed Gradient Descent
Guangliang Liu, Zhiyu Xue, Xitong Zhang +2
Fine-tuning pretrained language models (PLMs) for downstream tasks is a large-scale optimization problem, in which the choice of the training algorithm critically determines how we…
Implicit regularization in Heavy-ball momentum accelerated stochastic gradient descent
Avrajit Ghosh, He Lyu, Xitong Zhang +1
It is well known that the finite step-size () in Gradient Descent (GD) implicitly regularizes solutions to flatter minima. A natural question to ask is "Does the momentum parame…