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09/21/2023
Model-based Clustering using Non-parametric Hidden Markov Models
Thanks to their dependency structure, non-parametric Hidden Markov Model...
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06/28/2023
Frontiers to the learning of nonparametric hidden Markov models
Hidden Markov models (HMMs) are flexible tools for clustering dependent ...
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06/26/2023
Optimal estimation of high-order missing masses, and the rare-type match problem
Consider a random sample (X_1,…,X_n) from an unknown discrete distributi...
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03/11/2022
Bayesian Nonparametric Inference for "Species-sampling" Problems
"Species-sampling" problems (SSPs) refer to a broad class of statistical...
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07/02/2021
Asymptotic Analysis of Statistical Estimators related to MultiGraphex Processes under Misspecification
This article studies the asymptotic properties of Bayesian or frequentis...
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06/24/2021
Fundamental limits for learning hidden Markov model parameters
We study the frontier between learnable and unlearnable hidden Markov mo...
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04/07/2021
Near-optimal estimation of the unseen under regularly varying tail populations
Given n samples from a population of individuals belonging to different ...
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12/31/2019
Asymptotic Risk of Least Squares Minimum Norm Estimator under the Spike Covariance Model
One of the recent approaches to explain good performance of neural netwo...
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02/14/2019
Optimal disclosure risk assessment
Protection against disclosure is a legal and ethical obligation for agen...
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05/15/2018
Adaptive Bayesian semiparametric density estimation in sup-norm
We investigate the problem of deriving adaptive posterior rates of contr...
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12/06/2017
Exchangeable modelling of relational data: checking sparsity, train-test splitting, and sparse exchangeable Poisson matrix factorization
A variety of machine learning tasks---e.g., matrix factorization, topic ...
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12/05/2017
