Preprints

  1. Elisabeth Gassiat, Ibrahim Kaddouri, Zacharie Naulet. “Model-based Clustering using Non-parametric Hidden Markov Models”. 2023. https://arxiv.org/abs/2309.12238.
  2. Kweku Abraham, Elisabeth Gassiat, Zacharie Naulet. “Frontiers to the learning of nonparametric hidden Markov models”. 2023. https://arxiv.org/abs/2306.16293.
  3. Stefano Favaro, Zacharie Naulet. “Optimal estimation of high-order missing masses, and the rare-type match problem”. 2023. https://arxiv.org/abs/2306.14998.
  4. Cecilia Balocchi, Stefano Favaro, Zacharie Naulet. “Bayesian Nonparametric Inference for ‘Species-sampling’ problems”. 2022. https://arxiv.org/abs/2203.06076.
  5. Yasaman Mahdaviyeh, Zacharie Naulet. “Risk of the least squares minimum norm estimator under the spike covariance model”. 2019. https://arxiv.org/abs/1912.13421.
  6. Victor Veitch, Ekansh Sharma, Zacharie Naulet, Daniel M Roy. “Exchangeable modelling of relational data: checking sparsity, train-test splitting, and sparse exchangeable Poisson matrix factorization”. 2017. https://arxiv.org/abs/1712.02311.

List of publications

  1. Julyan Arbel, Hong-Phuong Dang, Clément Elvira, Cédric Herzet, Zacharie Naulet and Mariia Vladimirova. “Bayes in action in deep learning and dictionary learning”. ESAIM: ProcS 74 (2023) 90–107. https://doi.org/10.1051/proc/202374090.
  2. Zacharie Naulet, Judith Rousseau, François Caron. “Asymptotic analysis of statistical estimators related to multigraphex processes under misspecification”. To appear in Bernoulli. https://arxiv.org/abs/2107.01120.
  3. Stefano Favaro, Zacharie Naulet. “Near-optimal estimation of the unseen under regularly varying tail populations”. Bernoulli 29 (4) 3423–3442, 2023. http://dx.doi.org/10.3150/23-BEJ1589.
  4. Kweku Abraham, Elisabeth Gassiat, Zacharie Naulet. “Fundamental limits for learning hidden Markov model parameters”. IEEE Transactions on Information Theory. 2022. https://doi.org/10.1109/TIT.2022.3213429.
  5. Zacharie Naulet. “Adaptive Bayesian density estimation in sup-norm”. Bernoulli 28 (2) 1284–1308, May 2022. https://doi.org/10.3150/21-BEJ1387.
  6. Federico Camerlenghi, Stefano Favaro, Zacharie Naulet, Francesca Panero. “Optimal disclosure risk assessment”. Ann. Statist. 49 (2) 723–744, April 2021. https://doi.org/10.1214/20-AOS1975.
  7. Zacharie Naulet, Daniel M Roy, Ekansh Sharma, Victor Veitch. “Bootstrap estimators for the tail-index and the count statistics of graphex processes”. Electron. J. Statist. 15 (1) 282–325, 2021. https://doi.org/10.1214/20-EJS1789.
  8. Zacharie Naulet, Eric Barat. “Some aspects of symmetric Gamma Process mixtures”. Bayesian Anal. 13 (3) 703–720, September 2018. https://doi.org/10.1214/17-BA1058.
  9. Zacharie Naulet, Judith Rousseau. “Posterior concentration rates for mixtures of normals in random design regression”. Electron. J. Statist. 11 (2) 4065–4102, 2017. https://doi.org/10.1214/17-EJS1344.
  10. Zacharie Naulet, Eric Barat. “Bayesian nonparametric estimation for Quantum Homodyne Tomography”. Electron. J. Statist. 11 (2) 3595–3632, 2017. https://doi.org/10.1214/17-EJS1322.
  11. Zacharie Naulet, Eric Barat. “Signal stochastic decomposition over continuous dictionaries”. 2014 IEEE International Workshop on Machine Learning for Signal Processing (MLSP). 2014. https://doi.org/10.1109/MLSP.2014.6958857.