Aggregation by Exponential Weighting and Sharp Oracle Inequalities. - Arnak S. Dalalyan; Alexandre B. Tsybakov (COLT, 2007)

A New Algorithm for Estimating the Effective Dimension-Reduction Subspace. - Arnak S. Dalalyan; Anatoli B. Juditsky; Vladimir G. Spokoiny (J. Mach. Learn. Res., 2008)

Aggregation by exponential weighting, sharp PAC-Bayesian bounds and sparsity. - Arnak S. Dalalyan; Alexandre B. Tsybakov (Mach. Learn., 2008)

Sparse learning approach to the problem of robust estimation of camera locations. - Arnak S. Dalalyan; Renaud Keriven (ICCV Workshops, 2009)

L1-Penalized Robust Estimation for a Class of Inverse Problems Arising in Multiview Geometry. - Arnak S. Dalalyan; Renaud Keriven (NIPS, 2009)

Towards Optimal Naive Bayes Nearest Neighbor. - Régis Behmo; Paul Marcombes; Arnak S. Dalalyan; Véronique Prinet (ECCV (4), 2010)

Exploiting Loops in the Graph of Trifocal Tensors for Calibrating a Network of Cameras. - Jérôme Courchay; Arnak S. Dalalyan; Renaud Keriven; Peter F. Sturm (ECCV (2), 2010)

Competing against the Best Nearest Neighbor Filter in Regression. - Arnak S. Dalalyan; Joseph Salmon (ALT, 2011)

Image denoising with patch based PCA: local versus global. - Charles-Alban Deledalle; Joseph Salmon; Arnak S. Dalalyan (BMVC, 2011)

Tight conditions for consistent variable selection in high dimensional nonparametric regression. - Laëtitia Comminges; Arnak S. Dalalyan (COLT, 2011)

Optimal aggregation of affine estimators. - Joseph Salmon; Arnak S. Dalalyan (COLT, 2011)

Fused sparsity and robust estimation for linear models with unknown variance. - Arnak S. Dalalyan; Yin Chen (NIPS, 2012)

On Camera Calibration with Linear Programming and Loop Constraint Linearization. - Jérôme Courchay; Arnak S. Dalalyan; Renaud Keriven; Peter F. Sturm (Int. J. Comput. Vis., 2012)

Sparse regression learning by aggregation and Langevin Monte-Carlo. - Arnak S. Dalalyan; Alexandre B. Tsybakov (J. Comput. Syst. Sci., 2012)

Robust Estimation for an Inverse Problem Arising in Multiview Geometry. - Arnak S. Dalalyan; Renaud Keriven (J. Math. Imaging Vis., 2012)

Wilks' phenomenon and penalized likelihood-ratio test for nonparametric curve registration. - Arnak S. Dalalyan; Olivier Collier (AISTATS, 2012)

Permutation estimation and minimax rates of identifiability. - Olivier Collier; Arnak S. Dalalyan (AISTATS, 2013)

Learning Heteroscedastic Models by Convex Programming under Group Sparsity. - Arnak S. Dalalyan; Mohamed Hebiri; Katia Meziani; Joseph Salmon (ICML (3), 2013)

On the Exponentially Weighted Aggregate with the Laplace Prior. - Arnak S. Dalalyan; Edwin Grappin; Quentin Paris (CoRR, 2016)

Minimax Rates in Permutation Estimation for Feature Matching. - Olivier Collier; Arnak S. Dalalyan (J. Mach. Learn. Res., 2016)

Further and stronger analogy between sampling and optimization: Langevin Monte Carlo and gradient descent. - Arnak S. Dalalyan (COLT, 2017)

User-friendly guarantees for the Langevin Monte Carlo with inaccurate gradient. - Arnak S. Dalalyan; Avetik G. Karagulyan (CoRR, 2017)

On sampling from a log-concave density using kinetic Langevin diffusions. - Arnak S. Dalalyan; Lionel Riou-Durand (CoRR, 2018)

Outlier-robust estimation of a sparse linear model using ell_1-penalized Huber's M-estimator. - Arnak S. Dalalyan; Philip Thompson (NeurIPS, 2019)

Minimax rates in outlier-robust estimation of discrete models. - Amir-Hossein Bateni; Arnak S. Dalalyan (CoRR, 2019)

A nonasymptotic law of iterated logarithm for robust online estimators. - Victor-Emmanuel Brunel; Arnak S. Dalalyan; Nicolas Schreuder (CoRR, 2019)

Outlier-robust estimation of a sparse linear model using 𝓁1-penalized Huber's M-estimator. - Arnak S. Dalalyan; Philip Thompson (CoRR, 2019)

A nonasymptotic law of iterated logarithm for general M-estimators. - Arnak S. Dalalyan; Nicolas Schreuder; Victor-Emmanuel Brunel (AISTATS, 2020)

Penalized Langevin dynamics with vanishing penalty for smooth and log-concave targets. - Avetik G. Karagulyan; Arnak S. Dalalyan (NeurIPS, 2020)

Statistical guarantees for generative models without domination. - Nicolas Schreuder; Victor-Emmanuel Brunel; Arnak S. Dalalyan (ALT, 2021)

Optimal detection of the feature matching map in presence of noise and outliers. - Tigran Galstyan; Arshak Minasyan; Arnak S. Dalalyan (CoRR, 2021)

Risk bounds for aggregated shallow neural networks using Gaussian priors. - Laura Tinsi; Arnak S. Dalalyan (COLT, 2022)

Nearly minimax robust estimator of the mean vector by iterative spectral dimension reduction. - Amir-Hossein Bateni; Arshak Minasyan; Arnak S. Dalalyan (CoRR, 2022)

Bounding the Error of Discretized Langevin Algorithms for Non-Strongly Log-Concave Targets. - Arnak S. Dalalyan; Avetik G. Karagulyan; Lionel Riou-Durand (J. Mach. Learn. Res., 2022)

Matching Map Recovery with an Unknown Number of Outliers. - Arshak Minasyan; Tigran Galstyan; Sona Hunanyan; Arnak S. Dalalyan (AISTATS, 2023)

Graphon Estimation in bipartite graphs with observable edge labels and unobservable node labels. - Etienne Donier-Meroz; Arnak S. Dalalyan; Francis Kramarz; Philippe Choné; Xavier D'Haultfoeuille (CoRR, 2023)

Guaranteed Optimal Generative Modeling with Maximum Deviation from the Empirical Distribution. - Elen Vardanyan; Arshak Minasyan; Sona Hunanyan; Tigran Galstyan; Arnak S. Dalalyan (CoRR, 2023)

Langevin Monte Carlo for strongly log-concave distributions: Randomized midpoint revisited. - Lu Yu; Avetik G. Karagulyan; Arnak S. Dalalyan (ICLR, 2024)

Statistically Optimal Generative Modeling with Maximum Deviation from the Empirical Distribution. - Elen Vardanyan; Sona Hunanyan; Tigran Galstyan; Arshak Minasyan; Arnak S. Dalalyan (ICML, 2024)

Parallelized Midpoint Randomization for Langevin Monte Carlo. - Lu Yu; Arnak S. Dalalyan (CoRR, 2024)

Assessing the Quality of Denoising Diffusion Models in Wasserstein Distance: Noisy Score and Optimal Bounds. - Vahan Arsenyan; Elen Vardanyan; Arnak S. Dalalyan (CoRR, 2025)