Search Results for author:
Found 2 papers, 0 papers with code
No Dimensional Sampling Coresets for Classification
We refine and generalize what is known about coresets for classification problems via the sensitivity sampling framework.
Linear Distance Metric Learning with Noisy Labels
In linear distance metric learning, we are given data in one Euclidean metric space and the goal is to find an appropriate linear map to another Euclidean metric space which respects certain distance conditions as much as possible.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
