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Measure concentration through non-Lipschitz observables and functional inequalities

   
@article{EJP2425,
	author = {Aldéric Joulin and Arnaud Guillin},
	title = {Measure concentration through non-Lipschitz observables and functional inequalities},
	journal = {Electron. J. Probab.},
	fjournal = {Electronic Journal of Probability},
	volume = {18},
	year = {2013},
	keywords = {Concentration; invariant measure; reversible Markov process; Lyapunov condition; functional inequality; diffusion process; jump process},
	abstract = {Non-Gaussian concentration estimates are obtained for invariant probability measures of reversible Markov processes. We show that the functional inequalities approach combined with a suitable Lyapunov condition allows us to circumvent the classical Lipschitz assumption of the observables. Our method is general and offers an unified treatment of diffusions and pure-jump Markov processes on unbounded spaces.},
	pages = {no. 65, 1-26},
	issn = {1083-6489},
	doi = {10.1214/EJP.v18-2425},    
        url = {http://ejp.ejpecp.org/article/view/2425}}