Rebiha Zeghdane

Adaptive-batch stochastic gradient descent for constrained optimization based on relaxed barrier functions

Stochastic Gradient Descent (SGD) is the cornerstone of large-scale optimization; however, its application to problems with a vast number of constraints remains a significant challenge. Methods based on relaxed logarithmic barrier functions have enabled the use of SGD by sampling...

Robust stochastic gradient descent for linearly constrained problems via adaptive barrier amplification

Methods based on Stochastic Gradient Descent using relaxed barrier functions provide a powerful framework for linearly constrained optimization but often suffer from sensitivity to hyperparameter settings and slow recovery from infeasible regions. Our investigation reveals that t...