CONGO: Compressive Online Gradient Optimization with Application to
Microservices Management
CONGO: Compressive Online Gradient Optimization with Application to
Microservices Management
We address the challenge of online convex optimization where the objective function's gradient exhibits sparsity, indicating that only a small number of dimensions possess non-zero gradients. Our aim is to leverage this sparsity to obtain useful estimates of the objective function's gradient even when the only information available is a …