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cs.LG2022
Efficient Convex Optimization Requires Superlinear Memory
Annie Marsden, Vatsal Sharan, Aaron Sidford +1
We show that any memory-constrained, first-order algorithm which minimizes -dimensional, -Lipschitz convex functions over the unit ball to accuracy using…
cs.LG2022
KL Divergence Estimation with Multi-group Attribution
Parikshit Gopalan, Nina Narodytska, Omer Reingold +2
Estimating the Kullback-Leibler (KL) divergence between two distributions given samples from them is well-studied in machine learning and information theory. Motivated by considera…