Results 11 to 20 of about 7,015 (298)
A Markov–Dobrushin Inequality for Quantum Channels
We propose a quantum extension of the Markov-Dobrushin inequality. As an application, we estimate the Markov-Dobrushin constant for some classes of quantum Markov channels, in particular for the Pauli channel, widely studied in quantum information theory.
Luigi Accardi +2 more
openaire +3 more sources
On the Markov inequality in L-spaces
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Goetgheluck, P
openaire +3 more sources
On Markov′s Inequality on R for the Hermite Weight
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Li, X. +2 more
openaire +4 more sources
Transportation inequalities for Markov kernels and their applications [PDF]
38 pages.
Baudoin, Fabrice, Eldredge, Nathaniel
openaire +4 more sources
An extremal inequality for long Markov chains [PDF]
18 pages, 1 figure.
Thomas A. Courtade, Jiantao Jiao
openaire +2 more sources
Exponential inequalities for nonstationary Markov chains [PDF]
Abstract Exponential inequalities are main tools in machine learning theory. To prove exponential inequalities for non i.i.d random variables allows to extend many learning techniques to these variables. Indeed, much work has been done both on inequalities and learning theory for time series, in the past 15 years.
Alquier Pierre +2 more
openaire +3 more sources
On Chebyshev–Markov–Krein inequalities
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Allan Pinkus, José M. Quesada
openaire +2 more sources
Markov’s inequality and polynomial mappings [PDF]
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openaire +3 more sources
Weighted Markov Inequality on Several Intervals
In this study we give a weighted Markov inequality on several ...
Akturk, Mehmet Ali, Lukashov, Alexey
core +1 more source
Abstract When deploying mobile robots in real‐world scenarios, such as airports, train stations, hospitals, and schools, collisions with pedestrians are intolerable and catastrophic. Motion safety becomes one of the most fundamental requirements for mobile robots.
Zhiqian Zhou +7 more
wiley +1 more source

