Results 271 to 280 of about 4,221,495 (320)

A novel ensemble-based genetic algorithm for enhanced feature selection in lung and pancreatic cancer diagnosis. [PDF]

Discov Oncol
Shabir S, Chishti MA.
europepmc   +1 more source

Parabolic-elliptic and indirect-direct simplifications in chemotaxis systems driven by indirect signalling. [PDF]

Calc Var Partial Differ Equ
Bui LTT, Huynh TKL, Tang BQ, Tran BN.
europepmc   +1 more source

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Uniform Convergence

Mathematical Analysis, 2021
Let E be a set and Y be a metric space. Consider functions fn : E → Y for n = 1, 2, . . . . We say that the sequence (fn) converges pointwise on E if there is a function f : E → Y such that fn(p) → f(p) for every p ∈ E.
John Quigg
semanticscholar   +3 more sources

Uniform Continuity, Uniform Convergence, and Shields

Set-Valued and Variational Analysis, 2010
The authors study uniform continuity and uniform convergence in metric spaces using the notion of shields. A superset \(A_1\) of a nonempty subset \(A\) in a metric space \((X,d)\) is called a shield for \(A\) if \(C\cap A_1=\emptyset\) and \(C\) is closed in \(X\) imply that \(C\cap A{^\epsilon}=\emptyset\) for some \(\epsilon > 0\), where \(A ...
Gerald Beer
exaly   +2 more sources

Uniform convergence rates for nonparametric estimators smoothed by the beta kernel

Scandinavian Journal of Statistics, 2022
This paper provides a set of uniform consistency results with rates for nonparametric density and regression estimators smoothed by the beta kernel having support on the unit interval.
Masayuki Hirukawa, Irina Murtazashvili, Artem B. Prokhorov   +2 more
semanticscholar   +1 more source

Uniform convergence

The Student Mathematical Library, 2018

semanticscholar   +2 more sources

On Uniform Convergence Structures

Mathematische Nachrichten, 1987
The authors study the problem of uniformization of arbitrary convergences. Their lattice-oriented approach, based on coilomorphisms (developed by \textit{S. Dolecki} and \textit{G. H. Greco}, Math. Nachr. 126, 327-348 (1986; Zbl 0604.54005)], gives a nice unified treatment and solution of this problem.
Lechicki, Alojzy, Ziemińska, Jolanta
openaire   +1 more source

List Sample Compression and Uniform Convergence

Annual Conference Computational Learning Theory
List learning is a variant of supervised classification where the learner outputs multiple plausible labels for each instance rather than just one. We investigate classical principles related to generalization within the context of list learning.
Steve Hanneke, Shay Moran, Tom Waknine
semanticscholar   +1 more source