no code implementations • 19 Jul 2022 • Antonio Blanca, Zongchen Chen, Daniel Štefankovič, Eric Vigoda
We consider a significantly weaker conditional sampling oracle, which we call the $\mathsf{Coordinate\ Oracle}$, and provide a computational and statistical characterization of the identity testing problem in this new model.
no code implementations • 12 Mar 2021 • Antonio Blanca, Pietro Caputo, Zongchen Chen, Daniel Parisi, Daniel Štefankovič, Eric Vigoda
For general spin systems, we prove that a contractive coupling for any local Markov chain implies optimal bounds on the mixing time and the modified log-Sobolev constant for a large class of Markov chains including the Glauber dynamics, arbitrary heat-bath block dynamics, and the Swendsen-Wang dynamics.
Probability Discrete Mathematics Data Structures and Algorithms Mathematical Physics Functional Analysis Mathematical Physics
no code implementations • 22 Apr 2020 • Antonio Blanca, Zongchen Chen, Daniel Štefankovič, Eric Vigoda
Daskalakis et al. (2018) presented a polynomial-time algorithm for identity testing for the ferromagnetic (attractive) Ising model.
no code implementations • 22 Jan 2019 • Ivona Bezakova, Antonio Blanca, Zongchen Chen, Daniel Štefankovič, Eric Vigoda
In particular, we prove hardness results in two prototypical cases, the Ising model and proper colorings, and explore whether identity testing is any easier than structure learning.
no code implementations • 17 Aug 2017 • Antonio Blanca, Zongchen Chen, Daniel Štefankovič, Eric Vigoda
We prove that in the tree uniqueness region (when $q>d$) the problem is identifiable and we can learn $G$ in ${\rm poly}(d, q) \times O(n^2\log{n})$ time.