5 citations · 7 across the 8 of their papers we have counts for
10 papers
Triangle-Free Coloring in LOCAL via Resilient Lovász Local Lemma
Peter Davies-Peck, Xusheng Zhang
The Lovász Local Lemma (LLL) is a probabilistic tool that has been shown to be of central importance in the study of distributed algorithms. For example, the constructive LLL is kn…
Fast Mixing for Low-Temperature Potts Models via Poisson Trees
Zongchen Chen, Andreas Galanis, Leslie Ann Goldberg +3
The -state ferromagnetic Potts model on a graph is a probability distribution on all -colourings of that favours many monochromatic edges. Approximate sampling from t…
Uniqueness and Mixing in the Low-Temperature Random-Cluster Model on Trees and Random Graphs
Antonio Blanca, Reza Gheissari, Heehyun Park +1
We study the random-cluster model on trees and treelike graphs at low temperatures. This is a model of dependent percolation parametrized by an edge probability and a…
Time-varying Mixing Matrix Design for Energy-efficient Decentralized Federated Learning
Xusheng Zhang, Tuan Nguyen, Ting He
We consider the design of mixing matrices to minimize the operation cost for decentralized federated learning (DFL) in wireless networks, with focus on minimizing the maximum per-n…
One-Shot Learning for k-SAT
Andreas Galanis, Leslie Ann Goldberg, Xusheng Zhang
Consider a -SAT formula where every variable appears at most times. Let be a satisfying assignment, sampled proportionally to where is the number…
Mean-field Potts and random-cluster dynamics from high-entropy initializations
Antonio Blanca, Reza Gheissari, Xusheng Zhang
A common obstruction to efficient sampling from high-dimensional distributions with Markov chains is the multimodality of the target distribution because they may get trapped far f…
Energy-efficient Decentralized Learning via Graph Sparsification
Xusheng Zhang, Cho-Chun Chiu, Ting He
This work aims at improving the energy efficiency of decentralized learning by optimizing the mixing matrix, which controls the communication demands during the learning process. T…
Diameters of symmetric and lifted simple exclusion models
Xusheng Zhang, Werner Krauth
We determine diameters of Markov chains describing one-dimensional N -particle models with an exclusion interaction, namely the Ssep (symmetric simple exclusion process) and one of…
Rapid mixing of global Markov chains via spectral independence: the unbounded degree case
Antonio Blanca, Xusheng Zhang
We consider spin systems on general -vertex graphs of unbounded degree and explore the effects of spectral independence on the rate of convergence to equilibrium of global Marko…
The Critical Mean-field Chayes-Machta Dynamics
Antonio Blanca, Alistair Sinclair, Xusheng Zhang
The random-cluster model is a unifying framework for studying random graphs, spin systems and electrical networks that plays a fundamental role in designing efficient Markov Chain…