3 citations · 5 across the 4 of their papers we have counts for
4 papers
Improving Generalization of Complex Models under Unbounded Loss Using PAC-Bayes Bounds
Xitong Zhang, Avrajit Ghosh, Guangliang Liu +1
Previous research on PAC-Bayes learning theory has focused extensively on establishing tight upper bounds for test errors. A recently proposed training procedure called PAC-Bayes t…
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…
Learning Sparsity-Promoting Regularizers using Bilevel Optimization
Avrajit Ghosh, Michael T. McCann, Madeline Mitchell +1
We present a method for supervised learning of sparsity-promoting regularizers for denoising signals and images. Sparsity-promoting regularization is a key ingredient in solving mo…
Bilevel learning of l1-regularizers with closed-form gradients(BLORC)
Avrajit Ghosh, Michael T. Mccann, Saiprasad Ravishankar
We present a method for supervised learning of sparsity-promoting regularizers, a key ingredient in many modern signal reconstruction problems. The parameters of the regularizer ar…