R.Frey, Risk minimization with incomplete information in a model for high-frequency data,Risk minimization with incomplete information in a model for high-frequency data - Frey - 2000 () Citation Context ...ring has been applied very successfully to pricing, hedging, and parameter-estimation ...
Machine learning offers an intriguing alternative to first-principle analysis for discovering new physics from experimental data. However, to date, purely data-driven methods have only proven successful in uncovering physical laws describing simple, low-
Spectral-Element Simulations of Wave Propagation in Porous Media: Finite-Frequency Sensitivity Kernels Based Upon Adjoint Methods The mathematical formulation of wave propagation in porous media developed by Biot is based upon the principle of virtual work, ignoring processes at the m... C Morency,J...
General linear models were used to analyze the experimental data sets in each year. We tested main and interactive effects, as well as a priori contrasts for specific treatment differences in 2009, as specified below. All models analyzed daughter frequency (dependent variable) as a function of ...
However, high frequency in high-risk sites, low rates of previous biopsy, and substantial variation in performance between physicians and clinics suggests there is significant opportunity to further improve health outcomes. Skin cancer is the most common cancer in Australia.1 Nonmelanoma skin cancer (...
Methods such as Neural Radiance Fields (Mildenhall et al., 2020) also inherently have a smoothness bias that lets them avoid degenerate solutions that may result from the shape-radiance ambiguity (Zhang et al., 2020) and can require positional encoding for high-frequency details (Tancik et al...
Examples include hop period and timing estimation, wherein hops may be missed at the output of the frequency discriminator or the emitter may hop out of band; Pulse Repetition Interval (PRI) analysis; and passive rotating-beam radio scanning. We study several pertinent period estimators. Our ...
Many notable advances in modern signal processing are based on the fact that even high-dimensional data follows a low complexity model. One such model, which has become an important prior for many signal processing tasks ranging from denoising and compressed sensing to super resolution, inpainting ...
The incomplete Airy integrals serve as canonical functions for the uniform ray optical solutions to several high-frequency scattering and diffraction problems that involve a class of integrals characterized by two stationary points that are arbitrarily close to one another or to an integration endpoint....
Radiofrequency ablation (RFA) promotes tumor antigen-specific T cell responses and enhances the effect of immunotherapy in preclinical settings. Here we report that the existence of remnant tumor masses due to incomplete RFA (iRFA) is associated with ear