Another example is when expected advertising revenue if we set τ = max{f(X): X U}, SCP asks to find the set of minimum size in U that achieves measure how effectively a subset X summarizes the entire dataset U [Tschiatschek et al., 2014].

Third, we are the first to consider regularized monotone SCP (RMSCP).

We consider the problem of discretization of neural operators between Hilbert spaces in a general framework including skip connections. We focus on bijec-tive neural operators through the lens of diffeomorphisms in infinite dimensions.

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Recently, the anchor acceleration, an acceleration mechanism distinct from Nes-terov's, has been discovered for minimax optimization and fixed-point problems,

While our presentation focuses on this finite-sum structure, most of our convergence results can easily be adapted to the general stochastic setting (see App. D).