Conditional-mean least-squares fitting of Gaussian Markov random fields to Gaussian fields. - Noel Cressie; Nicolas Verzelen (Comput. Stat. Data Anal., 2008)

Tests for Gaussian graphical models. - Nicolas Verzelen; Fanny Villers (Comput. Stat. Data Anal., 2009)

Data-driven neighborhood selection of a Gaussian field. - Nicolas Verzelen (Comput. Stat. Data Anal., 2010)

Partial recovery bounds for clustering with the relaxed K-means. - Christophe Giraud 002; Nicolas Verzelen (CoRR, 2018)

Information-Theoretic Bounds and Phase Transitions in Clustering, Sparse PCA, and Submatrix Localization. - Jess Banks; Cristopher Moore; Roman Vershynin; Nicolas Verzelen; Jiaming Xu 002 (IEEE Trans. Inf. Theory, 2018)

Active Ranking of Experts Based on their Performances in Many Tasks. - El Mehdi Saad; Nicolas Verzelen; Alexandra Carpentier (ICML, 2023)

Covariance-adaptive best arm identification. - El Mehdi Saad; Gilles Blanchard; Nicolas Verzelen (NeurIPS, 2023)

Computation-information gap in high-dimensional clustering. - Bertrand Even; Christophe Giraud 002; Nicolas Verzelen (COLT, 2024)

On Weak Regret Analysis for Dueling Bandits. - El Mehdi Saad; Alexandra Carpentier; Tomás Kocák; Nicolas Verzelen (NeurIPS, 2024)

Optimal rates for ranking a permuted isotonic matrix in polynomial time. - Emmanuel Pilliat; Alexandra Carpentier; Nicolas Verzelen (SODA, 2024)

Active clustering with bandit feedback. - Victor Thuot; Alexandra Carpentier; Christophe Giraud 002; Nicolas Verzelen (CoRR, 2024)

Optimal level set estimation for non-parametric tournament and crowdsourcing problems. - Maximilian Graf; Alexandra Carpentier; Nicolas Verzelen (CoRR, 2024)

Clustering with bandit feedback: breaking down the computation/information gap. - Victor Thuot; Alexandra Carpentier; Christophe Giraud 002; Nicolas Verzelen (ALT, 2025)

Clustering Items through Bandit Feedback: Finding the Right Feature out of Many. - Maximilian Graf; Victor Thuot; Nicolas Verzelen (CoRR, 2025)