9 citations · 9 across the 3 of their papers we have counts for
4 papers · 1 filter
Sharp multiple testing boundary for sparse sequences
Kweku Abraham, Ismael Castillo, Etienne Roquain
This work investigates multiple testing by considering minimax separation rates in the sparse sequence model, when the testing risk is measured as the sum FDR+FNR (False Discovery…
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…
Empirical Bayes cumulative -value multiple testing procedure for sparse sequences
Kweku Abraham, Ismael Castillo, Etienne Roquain
In the sparse sequence model, we consider a popular Bayesian multiple testing procedure and investigate for the first time its behaviour from the frequentist point of view. Given a…
Multiple Testing in Nonparametric Hidden Markov Models: An Empirical Bayes Approach
Kweku Abraham, Ismael Castillo, Elisabeth Gassiat
Given a nonparametric Hidden Markov Model (HMM) with two states, the question of constructing efficient multiple testing procedures is considered, treating one of the states as an…