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Found 4 papers, 3 papers with code
Randomized Greedy Algorithms and Composable Coreset for k-Center Clustering with Outliers
Though a number of methods have been developed in the past decades, it is still quite challenging to design quality guaranteed algorithm with low complexity for this problem.
Coresets for Wasserstein Distributionally Robust Optimization Problems
Though it is challenging to obtain a conventional coreset for \textsf{WDRO} due to the uncertainty issue of ambiguous data, we show that we can compute a ``dual coreset'' by using the strong duality property of \textsf{WDRO}.
Coresets for Relational Data and The Applications
A coreset is a small set that can approximately preserve the structure of the original input data set.
A Novel Sequential Coreset Method for Gradient Descent Algorithms
A wide range of optimization problems arising in machine learning can be solved by gradient descent algorithms, and a central question in this area is how to efficiently compress a large-scale dataset so as to reduce the computational complexity.
