We consider the high-dimensional inference problem where the signal is a low-rank
symmetric matrix which is corrupted by an additive Gaussian noise. Given a probabilistic …

We consider the sparse stochastic block model in the case where the degrees are
uninformative. The case where the two communities have approximately the same size has …

This article unveils a new relation between the Nishimori temperature parametrizing a
distribution P and the Bethe free energy on random Erdős–Rényi graphs with edge weights …

Spectral methods are popular in detecting global structures in the given data that can be
represented as a matrix. However when the data matrix is sparse or noisy, classic spectral …

This work considers clustering nodes of a largely incomplete graph. Under the problem
setting, only a small amount of queries about the edges can be made, but the entire graph is …

We consider the problem of clustering partially labeled data from a minimal number of
randomly chosen pairwise comparisons between the items. We introduce an efficient local …

社区结构是复杂网络的重要特征之一, 社区发现对研究网络结构有重要的应用价值.
基于非负矩阵分解(Non-negative Matrix Factorization, NMF) 的社区发现方法是解决社区发现 …

We revisit classical bounds of Fisher on the ferromagnetic Ising model (Fisher 1967 Phys.
Rev. 162 480), and show how to efficiently use them on an arbitrary given graph to …

We study classical statistical problems such as as community detection on graphs, Principal
Component Analysis (PCA), sparse PCA, Gaussian mixture clustering, linear and …

In an era of unprecedented deluge of (mostly unstructured) data, graphs are proving more
and more useful, across the sciences, as a flexible abstraction to capture complex …