The left side shows the effect of pruning of neurons in the weight-matrix of afully-connected layer. The rows in white correspond to neurons pruned in theassociated layer while thecolumns inwhite represent theeffectofremoving neurons from the previous layers. On the right, we allude to the possibility of collapsing the pruned matrix into a smaller,denseone.

Algorithms, while straightforward in theory, become challenging to deploy in real-world scenarios.

Real-world problems such as ad allocation and matching havebeen extensively studied under the lens of combinatorial optimization. In several applications, uncertainty in the input appears naturally and this has led to the study of online stochastic optimization models for such problems.