Search Results for author:
Found 3 papers, 0 papers with code
Local algorithms for interactive clustering
We study the design of interactive clustering algorithms for data sets satisfying natural stability assumptions.
Efficient Clustering with Limited Distance Information
Given a point set S and an unknown metric d on S, we study the problem of efficiently partitioning S into k clusters while querying few distances between the points.
Monotonic Calibrated Interpolated Look-Up Tables
Real-world machine learning applications may require functions that are fast-to-evaluate and interpretable.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
