R. Frey. Risk minimization with incomplete information in a model for high- frequency data. Mathematical Finance, 10(2):215-225, 2000.Frey, R.: 2000, Risk minimization with incomplete information in a model for high- frequency data, Mathematical Finance 10, 215-225....
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-
The first impres- sion is that on uncorrupted data, the three algorithms produce quite similar dictionaries, even though ITKrM produces more high-frequency atoms than KSVD and the first BPFA atoms clearly have the structure of the principle components used in the initialisation. The next obser- ...
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 a...
Later, after determining available data suggests endurance ratings aren'tproportionateto drive size, it was suggested the "current known worst case" for a 256GB drive would have it reach 100% in about two years. As to why the high disk usage has occurred, a likely culprit could be...
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Pulling Data Into a Second Survey (Longitudinal Surveys) Panel Company Integration Creating an Anonymized Raffle A/B Testing in Surveys Appointment / Event Registration Surveys Tickets Ask the Experts Ticketing Queue Closing the Loop Employee Experience Running a Pulse Program with a Hierarchy (EX...
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...
It may also be difficult, particularly in a market, such as agricultural commodities, to obtain data that is a sufficiently high frequency with reliability, to model and perform dynamic hedging. In our empirical study, we test static and dynamic cross-hedging for the Black-Scholes approach, min...
Moreover, repeated message passing can cause over-smoothing, reducing their capacity to preserve essential high-frequency details. To address these issues, we propose a Spectral Domain Reconstruction Graph Neural Network (SDR-GNN) for incomplete multimodal learning in conversational emotion recognition. ...