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cs.LG2026
Active Learning with Low-Rank Structure for Data Selection
Vincent Cohen-Addad, Sasidhar Kunapuli, Vahab Mirrokni +3
In the data selection problem, the objective is to choose a small, representative subset of data that can be used to efficiently train a machine learning model. Sener and Savarese…
cs.LG2026
Better Bounds for the Distributed Experts Problem
David P. Woodruff, Samson Zhou
In this paper, we study the distributed experts problem, where experts are distributed across servers for timesteps. The loss of each expert at each time is the $\e…
cs.LG2024
On Socially Fair Low-Rank Approximation and Column Subset Selection
Zhao Song, Ali Vakilian, David P. Woodruff +1
Low-rank approximation and column subset selection are two fundamental and related problems that are applied across a wealth of machine learning applications. In this paper, we stu…