Appendices for PLUGIn: A simple algorithm for inverting generative models with recovery guarantees A Some Results on Gaussian Matrices
–Neural Information Processing Systems
Here we state some results on Gaussian Matrices, which will be used in the proofs later. The following theorem is the concentration of (Gaussian) measure inequality for Lipschitz functions. Here we only state a one-sided version, though it is more commonly stated with a two-sided one, i.e., The result follows since E k A k p m + p n (see, e.g., [31, Section 7.3]). In particular, the following Bernstein's Inequality [31, Section 2.8] holds: P First, we establish that Z ( u, v; w) has a mixed tail. Next, by induction on k (i.e., apply (12) with r = r ( i 1) The result then follows by induction.
Neural Information Processing Systems
Nov-15-2025, 17:49:00 GMT
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