Maxim Raginsky
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| title | conference | date |
|---|---|---|
| Sampling Using Diffusion Processes, from Langevin to Schrödinger | Geometric Methods in Optimization and Sampling Boot Camp | 2021-08-30 |
Derives an explicit time‑dependent drift that exactly transports Brownian noise to a target law at t=1 by minimizing path‑space KL (the Schrodinger bridge)… | ||
| Strong Data Processing Inequalities: Applications to MCMC and Graphical Models | Information Theory, Learning and Big Data (Simons Institute, 2015) | 2015-03-16 |
Defines a pointwise strong data processing inequality (SDPI) for phi‑divergences, proves a general lower bound eta_phi(mu,K) ≥ eta_chi^2(mu,K) (chi^2 SDPI… | ||
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