This article studies an asymptotic framework for conducting inference on parameters of the form ϕ(θ₀), where ϕ is a known directionally differentiable function and θ₀ is estimated by θ̂n. In these ...

Let X be a normed linear space, Un an n-dimensional Chebyshev subspace of X. For f ∈ X denote by p(f) ∈ Un its best approximation in Un. The problem of strong unicity consists in estimating how fast ...

Provides a rigorous treatment of topics covered in Calculus 1 and 2. Topics include convergent sequences; continuous functions; differentiable functions; Darboux sums, Riemann sums, and integration; ...

We saw in the previous lecture that perceptrons have limited scope in the type of concepts they can learn - they can only learn linearly separable functions. However, we can think of constructing ...