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Found 6 papers, 0 papers with code
Binary perceptron: efficient algorithms can find solutions in a rare well-connected cluster
It was recently shown that almost all solutions in the symmetric binary perceptron are isolated, even at low constraint densities, suggesting that finding typical solutions is hard.
Proof of the Contiguity Conjecture and Lognormal Limit for the Symmetric Perceptron
We consider the symmetric binary perceptron model, a simple model of neural networks that has gathered significant attention in the statistical physics, information theory and probability theory communities, with recent connections made to the performance of learning algorithms in Baldassi et al. '15.
Ising model on trees and factors of IID
This model is known to be a factor of IID in the uniqueness regime, when the inverse temperature $\beta\ge 0$ satisfies $\tanh \beta \le (d-1)^{-1}$.
Probability Mathematical Physics Dynamical Systems Mathematical Physics 37A35, 37A50, 60G10, 60K35
Optimal Recovery of Block Models with $q$ Communities
This paper is motivated by the reconstruction problem on the sparse stochastic block model.
Probability Social and Information Networks
Learning Sparse Graphons and the Generalized Kesten-Stigum Threshold
The problem of learning graphons has attracted considerable attention across several scientific communities, with significant progress over the recent years in sparser regimes.
Spectral redemption: clustering sparse networks
Spectral algorithms are classic approaches to clustering and community detection in networks.
