Rademacher complexity is a more modern notion of complexity that is distribution dependent and defined for any class real-valued functions (not only discrete- ...

As an example, consider the rademacher and gaussian complexities of the L1 ball. The Rademacher complexity is given by exactly 1, whereas the Gaussian ... Using the Rademacher... · Bounding the Rademacher...

The Rademacher complexity of a feed-forward neural network can be bounded recursively by considering each layer at a time. A bound that can be used for the ...

21 мая 2020 г. · Therefore, the Rademacher complexity intuitively indicates how expressive the function class is. Rm({ca + b|a ∈ A}) = |c|Rm(A).

Rademacher complexity is a measure of the richness of a class of real-valued functions. In this sense, it is similar to the VC dimension.

We saw in Example 7.5 that the exact value is 1/2. The proof of Theorem 7.3 depends on yet another concentration of measure inequality for averages of random ...

25 сент. 2017 г. · Rademacher complexity can be used to derive sample complexity bounds for regression, classification with other loss functions like hinge ...

A uniform random variable X ∈ {−1,1} is called a Rademacher random variable. For any g ∈ G and m-sized sample T ∈ Zm, we denote by gT , (g(z1),...

The Rademacher Complexity of the hypothesis class H2 can be bounded by the maximum l2-norm of an instance from Hilbert space S devided by the square root of m, ...

17 апр. 2018 г. · We replace the expected value with the empirical average on another new imaginary sample and end up with this nice symmetric expression on the ...