7 citations · 17 across the 12 of their papers we have counts for
4 papers · 1 filter
SubSearch: Robust Estimation and Outlier Detection for Stochastic Block Models via Subgraph Search
Leonardo Martins Bianco, Christine Keribin, Zacharie Naulet
Community detection is a fundamental task in graph analysis, with methods often relying on fitting models like the Stochastic Block Model (SBM) to observed networks. While many alg…
Fundamental limits for learning hidden Markov model parameters
Kweku Abraham, Zacharie Naulet, Elisabeth Gassiat
We study the frontier between learnable and unlearnable hidden Markov models (HMMs). HMMs are flexible tools for clustering dependent data coming from unknown populations. The mode…
Risk of the Least Squares Minimum Norm Estimator under the Spike Covariance Model
Yasaman Mahdaviyeh, Zacharie Naulet
We study risk of the minimum norm linear least squares estimator in when the number of parameters depends on , and . We assume that data has…
Exchangeable modelling of relational data: checking sparsity, train-test splitting, and sparse exchangeable Poisson matrix factorization
Victor Veitch, Ekansh Sharma, Zacharie Naulet +1
A variety of machine learning tasks---e.g., matrix factorization, topic modelling, and feature allocation---can be viewed as learning the parameters of a probability distribution o…