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by Patrick LaVictoire 1196 days ago | link | parent

Note also that \(v_0(P)\) is maximized when \(P\) has full support on the distribution of \(Q\) and when \(s\) has a high average on \(P\). That is, it’s at most \(\epsilon\) from maximized when \(P\) is \((1-\epsilon)\) times a delta function on an \(s\)-maximizing point, plus \(\epsilon\) times the distribution of \(Q\).

So \(v_0\) essentially corresponds to a raw maximizer, and \(v_\alpha\) for \(0<\alpha<1\) interpolates between maximizing and softmax.



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