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SUMMARY:Langevin Monte Carlo Beyond Lipschitz Gradient Continuity - Błaż
 ej Miasojedow (University of Warsaw)
DTSTART:20241121T150000Z
DTEND:20241121T160000Z
UID:TALK223840@talks.cam.ac.uk
DESCRIPTION:We present a significant advancement in the field of Langevin 
 Monte Carlo (LMC) methods by introducing the Inexact Proximal Langevin Alg
 orithm (IPLA). This novel algorithm broadens the scope of problems that LM
 C can effectively address while maintaining controlled computational costs
 . IPLA extends LMC's applicability to potentials that are convex\, strongl
 y convex in the tails\, and exhibit polynomial growth\, beyond the convent
 ional $L$-smoothness assumption.&nbsp\;Moreover\, we extend LMC's applicab
 ility to super-quadratic potentials and offer improved convergence rates o
 ver existing algorithms. Additionally\, we provide bounds on all moments o
 f the Markov chain generated by IPLA\, enhancing its analytical robustness
 .\nThe talk is based on joint work with Matej Benko\, Iwona Chlebicka\, Jo
 rgen Endal.
LOCATION:Seminar Room 2\, Newton Institute
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