Nonlinear Perron-Frobenius theory and max-plus numerical methods for Hamilton-Jacobi equations

This problem has in particular been studied in the theory of empirical process (providing asymptotic results), and through statistical learning theory ([KOL 61],[VAP 71]). The

Jacobi equation. We take advantage of the methods of asymptotic analysis, convex analysis and of nonsmooth analysis to shed a new light on classical results. We use formulas of the

Among famous numerical methods (especially for Eikonal equations), remain the Fast Sweeping Method (FSM) and the Fast Marching Method (FMM). [34, 16, 49]) is based on an

These Pbx interacting partners, corresponding to homeodomain (Hox, Meis/Prep, Pdx1) and non- homeodomain (FoxC1, HPIP, ZFPIP, Smad, NR, MyoD) proteins, display more temporally

One could clearly hope for stronger results, but the above are already strong indications that when the data lie on a high-dimensional and curved manifold, local learning methods

This means that if the class distributions are such that there are many distinct regions with constant labels (either separated by low-density regions or regions with samples from

Comm. Viscosity solutions of a system of nonlinear second-order elliptic PDEs arising in switching games. On the rate of convergence of approximation schemes for Bellman

First, we prove a classification of boundary condition result for a nonconvex, coer- cive Hamiltonian, in the spirit of the flux-limited formulation for quasi-convex Hamilton-