Titlebook: Insurance, Biases, Discrimination and Fairness; Arthur Charpentier Book 2024 The Editor(s) (if applicable) and The Author(s), under exclus

Apogee

Post-Processing the predictions obtained, to make them “fair” (according to some specific criteria). As actuaries care about calibration, and the associated concept of a “well-balanced” model, quite naturally, we use averages and barycenters. Using optimal transport, we describe techniques, with strong mathematica

激勵(lì)

he valve had a diameter of 40mm, a 45° bevelled edge and was arranged at the exit of a straight tube of inside diameter 34mm with the lifts of 2, 4 and 6mm. Suction was applied by a variable speed electric fan to simulate the intake stroke of a cylinder of 400cc displacement at 1200 RPM, with an air

hypnotic

Arthur Charpentierhe valve had a diameter of 40mm, a 45° bevelled edge and was arranged at the exit of a straight tube of inside diameter 34mm with the lifts of 2, 4 and 6mm. Suction was applied by a variable speed electric fan to simulate the intake stroke of a cylinder of 400cc displacement at 1200 RPM, with an air

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Arthur Charpentieres.Will appeal to mathematicians and physicists whose researThis proceedings volume gathers selected, revised papers presented at the X International Meeting on Lorentzian Geometry (GeLoCor 2021), virtually held at the University of Córdoba, Spain, on February 1-5, 2021. It includes surveys describi

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helper-T-cells

gian approach to classical mechanics, the Lagrangian approach to classical field theory with examples taken from electrodynamics, general relativity and quantum mechanics. We then introduce the second quantization procedure to classical field theory wherein the field can be regarded as a countable e

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Arthur Charpentierd quantum nonlinear filtering techniques applied to problems of trajectory estimation in classical mechanical systems and maneouvering the motion of an aircraft, estimating observables in quantum mechanics like the spin of the electron from non-demolition measurements, adapting the least mean square