activity
20152021
most citedQuantum Monge-Kantorovich problem and transport distance between density matrices

32 citations · 76 across the 7 of their papers we have counts for

collaborators

7 papers

cs.DS2021

A Note on Projection-Based Recovery of Clusters in Markov Chains

Sam Cole

Let be the transition matrix of a purely clustered Markov chain, i.e. a direct sum of irreducible stochastic matrices. Given a perturbation of $T…

math.NA2021★ 1 cited

Clusters in Markov Chains via Singular Vectors of Laplacian Matrices

Sam Cole, Steve Kirkland

Suppose that is a stochastic matrix. We propose an algorithm for identifying clusters in the Markov chain associated with . The algorithm is recursive in nature, and in orde…

quant-ph2021★ 17 cited

Quantum Optimal Transport

Sam Cole, Michał Eckstein, Shmuel Friedland +1

We analyze a quantum version of the Monge--Kantorovich optimal transport problem. The quantum transport cost related to a Hermitian cost matrix is minimized over the set of all…

quant-ph2021★ 32 cited

Quantum Monge-Kantorovich problem and transport distance between density matrices

Shmuel Friedland, Michał Eckstein, Sam Cole +1

A quantum version of the Monge--Kantorovich optimal transport problem is analyzed. The transport cost is minimized over the set of all bipartite coupling states , such that…

cs.LG2018★ 26 cited

Exact Recovery in the Hypergraph Stochastic Block Model: a Spectral Algorithm

Sam Cole, Yizhe Zhu

We consider the exact recovery problem in the hypergraph stochastic block model (HSBM) with blocks of equal size. More precisely, we consider a random -uniform hypergraph $H…

cs.DS2017

Recovering Nonuniform Planted Partitions via Iterated Projection

Sam Cole

In the planted partition problem, the vertices of a random graph are partitioned into "clusters," and edges between vertices in the same cluster and different clusters are…

cs.DS2015

A Simple Spectral Algorithm for Recovering Planted Partitions

Sam Cole, Shmuel Friedland, Lev Reyzin

In this paper, we consider the planted partition model, in which vertices of a random graph are partitioned into "clusters," each of size . Edges between vertices i…