DeepAI AI Chat

On exact discretization of the L_2-norm with a negative weight

04/28/2021

∙

by I. V. Limonova, et al.

∙

∙

For a subspace X of functions from L_2 we consider the minimal number m of nodes necessary for the exact discretization of the L_2-norm of the functions in X. We construct a subspace such that for any exact discretization with m nodes there is at least one negative weight.

page 1

page 2

page 3

page 4

∙ 09/22/2020

On sampling discretization in L_2

A sampling discretization theorem for the square norm of functions from ...

0 Irina Limonova, et al. ∙

∙ 04/02/2021

A remark on discretization of the uniform norm

Discretization of the uniform norm of functions from a given finite dime...

0 Boris Kashin, et al. ∙

∙ 03/14/2022

Sampling discretization error of integral norms for function classes with small smoothness

We consider infinitely dimensional classes of functions and instead of t...

0 V. N. Temlyakov, et al. ∙

∙ 01/14/2023

Universal discretization and sparse sampling recovery

Recently, it was discovered that for a given function class 𝐅 the error ...

0 F. Dai, et al. ∙

∙ 02/12/2022

Impact of Discretization Noise of the Dependent variable on Machine Learning Classifiers in Software Engineering

Researchers usually discretize a continuous dependent variable into two ...

0 Gopi Krishnan Rajbahadur, et al. ∙

∙ 02/03/2020

Exponential discretization of weights of neural network connections in pre-trained neural networks

To reduce random access memory (RAM) requirements and to increase speed ...

0 Magomed Yu. Malsagov, et al. ∙

∙ 05/12/2020

Sampling discretization of integral norms of the hyperbolic cross polynomials

The paper is devoted to discretization of integral norms of functions fr...

0 Vladimir Temlyakov, et al. ∙