Ramon van Handel
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| title | conference | date |
|---|---|---|
| Remarks on the Discrete Cube | Probability, Geometry, and Computation in High Dimensions Boot Camp (Simons Institute, Fall 2020) | 2020-08-19 |
Provides a self-contained proof that Var(f) ≤ Σi E[(Di f)^2] with optimal constant 1 by building an interpolation by continuous-time random walk (independent… | ||
| Remarks on the Discrete Cube | Probability, Geometry, and Computation in High Dimensions Boot Camp (Simons Institute, Fall 2020) | 2020-08-19 |
Proves the Poincaré inequality on the discrete cube using an explicit semi-group Pt (a product formula with biased Bernoullis), computes D_t Pt = ΔPt and… | ||
| Remarks on the Discrete Cube | Probability, Geometry, and Computation in High Dimensions Boot Camp (Simons Institute, Fall 2020) | 2020-08-19 |
Shows the naive Gaussian→cube replacement fails: Talagrand’s L∞ counterexample forces a different formulation. Proves a precise linear→nonlinear principle on… | ||
| Remarks on the Discrete Cube | Probability, Geometry, and Computation in High Dimensions Boot Camp (Simons Institute, Fall 2020) | 2020-08-19 |
Boolean functions on the discrete cube beat the usual Poincaré bound by two mechanisms: replace L2 by an L1 Poincaré inequality to remove a square, and exploit… | ||
| How Large is the Norm of a Random Matrix? | Information Theory, Learning and Big Data (Simons Institute, 2015) | 2015-03-16 |
Gives matching upper and lower bounds for the expected spectral norm of an independent-entry Gaussian matrix in terms of two explicit parameters: the… | ||
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