MCMC methods for rare events and non-convex supports

Developing novel sampling methods, with applications to rare event sampling and stochastic optimization.

See below for the list of related publications and preprints.

Efficient sampling Applied Probability Global optimization
Alessandro Zocca
Alessandro Zocca
Tenured Assistant Professor

Related

Publications

Uncovering Load-Altering Attacks Against $N-1$ Secure Power Grids: A Rare-Event Sampling Approach (2023)

M. Goodridge, S. Lakshminarayana, A. Zocca Submitted to IEEE Transactions on Power Systems
How to identify the most impactful dynamic load-altering attacks?
arXiv preprint PDF bib

Analysis of Cascading Failures Due to Dynamic Load-Altering Attacks (2023)

M. Goodridge, A. Zocca, S. Lakshminarayana IEEE SmartGridComm 2023
What are the features of the most impactful dynamic load-altering attacks?
arXiv preprint PDF DOI BibTeX

Hopping between distant basins (2022)

M. Goodridge, J. Moriarty, J. Vogrinc, A. Zocca Journal of Global Optimization
How to improve the Basin Hopping method for global optimization with nonlocal random perturbations?
arXiv preprint PDF DOI bib

A Metropolis-class sampler for targets with non-convex support (2021)

J. Moriarty, J. Vogrinc, A. Zocca Statistics and Computing
How to efficiently sample from target densities with non-convex support? Introducing the Skipping Sampler
arXiv preprint PDF DOI bib

Frequency violations from random disturbances: an MCMC approach (2018)

J. Moriarty, J. Vogrinc, A. Zocca 2018 Conference on Decision and Control (CDC)
How to efficiently sample rare events in power systems? Introducing the Ghost Sampler
arXiv preprint PDF DOI bib