BalLOT: Balanced k-means clustering with optimal transport
BalLOT solves balanced k-means clustering by reformulating it as an optimal transport problem. It replaces slow methods like SDP and Hungarian algorithms with a fast alternating minimization approach. This method provides scalable solutions, offering near-linear runtime growth with respect to data size, making it effective for large datasets.