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- Emmanuel Abbe, Afonso S. Bandeira, Georgina Hall
- IEEE Transactions on Information Theory
- 2016

The stochastic block model with two communities, or equivalently the planted bisection model, is a popular model of random graph exhibiting a cluster behavior. In the symmetric case, the graph has two equally sized clusters and vertices connect with probability p within clusters and q across clusters. In the past two decades, a large body of literature in… (More)

- Emmanuel Abbe, Colin Sandon
- ArXiv
- 2015

New phase transition phenomena have recently been discovered for the stochastic block model, for the special case of two non-overlapping symmetric communities. This gives raise in particular to new algorithmic challenges driven by the thresholds. This paper investigates whether a general phenomenon takes place for multiple communities, without imposing… (More)

- Emmanuel Abbe, Afonso S. Bandeira, Annina Bracher, Amit Singer
- IEEE Transactions on Network Science and…
- 2014

We consider the problem of clustering a graph G into two communities by observing a subset of the vertex correlations. Specifically, we consider the inverse problem with observed variables Y = B<sub>G</sub>x ⊕ Z, where B<sub>G</sub> is the incidence matrix of a graph G, x is the vector of unknown vertex variables (with a uniform prior), and Z is a… (More)

- Emmanuel Abbe, Lizhong Zheng
- IEEE Transactions on Information Theory
- 2010

Over discrete memoryless channels (DMC), linear decoders (maximizing additive metrics) afford several nice properties. In particular, if suitable encoders are employed, the use of decoding algorithms with manageable complexities is permitted. For a compound DMC, decoders that perform well without the channel's knowledge are required in order to achieve… (More)

- Naveen Goela, Emmanuel Abbe, Michael Gastpar
- IEEE Transactions on Information Theory
- 2013

Polar codes are introduced for discrete memoryless broadcast channels. For m-user deterministic broadcast channels, polarization is applied to map uniformly random message bits from m-independent messages to one codeword while satisfying broadcast constraints. The polarization-based codes achieve rates on the boundary of the private-message capacity region.… (More)

- Emmanuel Abbe, Colin Sandon
- ArXiv
- 2015

In a paper that initiated the modern study of the stochastic block model, Decelle, Krzakala, Moore and Zdeborová made a fascinating conjecture: Denote by k the number of balanced communities, a/n the probability of connecting inside clusters and b/n across clusters, and set SNR = (a − b)/(k(a + (k − 1)b)); for any k ≥ 2, it is possible to detect efficiently… (More)

- Emmanuel Abbe
- ArXiv
- 2017

The stochastic block model (SBM) is a random graph model with planted clusters. It is widely employed as a canonical model to study clustering and community detection, and provides generally a fertile ground to study the statistical and computational tradeoffs that arise in network and data sciences. This note surveys the recent developments that establish… (More)

- Emmanuel Abbe, Colin Sandon
- 2015 IEEE 56th Annual Symposium on Foundations of…
- 2015

New phase transition phenomena have recently been discovered for the stochastic block model, for the special case of two non-overlapping symmetric communities. This gives raise in particular to new algorithmic challenges driven by the thresholds. This paper investigates whether a general phenomenon takes place for multiple communities, without imposing… (More)

- Emmanuel Abbe, Colin Sandon
- NIPS
- 2015

The stochastic block model (SBM) has recently gathered significant attention due to new threshold phenomena. However, most developments rely on the knowledge of the model parameters, or at least on the number of communities. This paper introduces efficient algorithms that do not require such knowledge and yet achieve the optimal information-theoretic… (More)

- Emmanuel Abbe, Andrea Montanari
- APPROX-RANDOM
- 2013

This paper studies a class of probabilistic models on graphs, where edge variables depend on incident node variables through a fixed probability kernel. The class includes planted constraint satisfaction problems (CSPs), as well as more general structures motivated by coding and community clustering problems. It is shown that under mild assumptions on the… (More)