Reduce end to end training time from days to hours (or hours to minutes), and energy requirements/costs by an order of magnitude using coresets and data selection.
For GRAD-MATCH method, there are weights associated with each data point in X(subset of training set). Do the weights have physical significance? for example, if the value of the weight is higher, the relevant selected data has the greater contribution to the residual?
During the iteration, the selective index is in the selected indices, so the iteration break. why this happen?
thanks@krishnatejakk