Browsing by Author "Ombrosi, S."
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Endpoint estimates, extrapolation for multilinear muckenhoupt classes, and applications
Li, K.; Martell, J.M.; Martikainen, H.; Ombrosi, S.; Vuorinen, E. (2019)In this paper we present the results announced in the recent work by the first, second, and fourth authors of the current paper concerning Rubio de Francia extrapolation for the socalled multilinear Muckenhoupt classes. ... 
Mixed weak type estimates: Examples and counterexamples related to a problem of E. Sawyer
Ombrosi, S.; Pérez, C. (20160101)In this paper we study mixed weighted weaktype inequal ities for families of functions, which can be applied to study classic operators in harmonic analysis. Our main theorem extends the key result from [CMP2]. 
On pointwise and weighted estimates for commutators of CalderónZygmund operators
Lerner, A. K; Ombrosi, S.; RiveraRíos, I.P. (2017)In recent years, it has been well understood that a CalderónZygmund operator T is pointwise controlled by a finite number of dyadic operators of a very simple structure (called the sparse operators). We obtain a similar ... 
Proof of an extension of E. Sawyer's conjecture about weighted mixed weaktype estimates
Li, K.; Ombrosi, S.; Pérez, C. (201809)We show that if $v\in A_\infty$ and $u\in A_1$, then there is a constant $c$ depending on the $A_1$ constant of $u$ and the $A_{\infty}$ constant of $v$ such that $$\Big\\frac{ T(fv)} {v}\Big\_{L^{1,\infty}(uv)}\le c\, ... 
Quantitative weighted mixed weaktype inequalities for classical operators
Ombrosi, S.; Pérez, C.; Recchi, J. (20160630)We improve on several mixed weak type inequalities both for the HardyLittlewood maximal function and for CalderónZygmund operators. These type of inequalities were considered by Muckenhoupt and Wheeden and later on by ... 
Weighted mixed weaktype inequalities for multilinear operators
Li, K.; Ombrosi, S.; Picardi, B. (2017)In this paper we present a theorem that generalizes Sawyer's classic result about mixed weighted inequalities to the multilinear context. Let $\vec{w}=(w_1,...,w_m)$ and $\nu = w_1^\frac{1}{m}...w_m^\frac{1}{m}$, the main ...