activity
20112020
most citedMAX 2-SAT with up to 108 qubits

61 citations · 89 across the 6 of their papers we have counts for

collaborators

7 papers

stat.ML2020

A Metric Space for Point Process Excitations

Myrl G. Marmarelis, Greg Ver Steeg, Aram Galstyan

A multivariate Hawkes process enables self- and cross-excitations through a triggering matrix that behaves like an asymmetrical covariance structure, characterizing pairwise intera…

cs.IT2018

Maximizing Multivariate Information with Error-Correcting Codes

Kyle Reing, Greg Ver Steeg, Aram Galstyan

Multivariate mutual information provides a conceptual framework for characterizing higher-order interactions in complex systems. Two well-known measures of multivariate information…

cs.CL2014★ 2 cited

Understanding confounding effects in linguistic coordination: an information-theoretic approach

Shuyang Gao, Greg Ver Steeg, Aram Galstyan

We suggest an information-theoretic approach for measuring stylistic coordination in dialogues. The proposed measure has a simple predictive interpretation and can account for vari…

cs.SI2013★ 15 cited

Phase Transitions in Community Detection: A Solvable Toy Model

Greg Ver Steeg, Cristopher Moore, Aram Galstyan +1

Recently, it was shown that there is a phase transition in the community detection problem. This transition was first computed using the cavity method, and has been proved rigorous…

quant-ph2013★ 61 cited

MAX 2-SAT with up to 108 qubits

Siddhartha Santra, Greg Quiroz, Greg Ver Steeg +1

We experimentally study the performance of a programmable quantum annealing processor, the D-Wave One (DW1) with up to 108 qubits, on maximum satisfiability problem with 2 variable…

cs.SI2011★ 5 cited

Information Transfer in Social Media

Greg Ver Steeg, Aram Galstyan

Recent research has explored the increasingly important role of social media by examining the dynamics of individual and group behavior, characterizing patterns of information diff…

physics.data-an2011★ 6 cited

Statistical Mechanics of Semi-Supervised Clustering in Sparse Graphs

Greg Ver Steeg, Aram Galstyan, Armen E. Allahverdyan

We theoretically study semi-supervised clustering in sparse graphs in the presence of pairwise constraints on the cluster assignments of nodes. We focus on bi-cluster graphs, and s…