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YearTypePublication
2024JournalAmir-Hossein Bateni and Arshak Minasyan and Arnak S. Dalalyan (2024). Nearly minimax robust estimator of the mean vector by iterative spectral dimension reduction. Bernoulli, to appear, arXiv(2204.02323), pp. 1-35. (link) (bib)
2024ConferenceLu Yu and Avetik G. Karagulyan and Arnak S. Dalalyan (2024). Langevin Monte Carlo for strongly log-concave distributions: Randomized midpoint revisited. In ICLR, pp. 1-10. (link) (bib)
2024ConferenceElen Vardanyan, Sona Hunanyan and Tigran Galstyan, Arshak Minasyan and Arnak S. Dalalyan (2024). Statistically Optimal Generative Modeling with Maximum Deviation from the Empirical Distribution. In ICML, pp. 1-8. (link) (bib)
2024Technical reportLu Yu, Arnak S. Dalalyan (2024). Parallelized Midpoint Randomization for Langevin Monte Carlo. arXiv. 2402.14434. submitted. (link) (bib)
2023JournalArnak S. Dalalyan (2023). Simple Proof of the Risk Bound for Denoising by Exponential Weights for Asymmetric Noise Distributions. Journal of Contemporary Mathematical Analysis (Armenian Academy of Sciences), 58(6), pp. 391-399. (link) (bib)
2023ConferenceArshak Minasyan and Tigran Galstyan and Sona Hunanyan and Arnak S. Dalalyan (2023). Matching Map Recovery with an Unknown Number of Outliers. In AISTATS, pp. 891–906. (link) (bib)
2023Technical reportEtienne Donier-Meroz, Arnak S. Dalalyan, Francis Kramarz, Philippe Choné, Xavier D'Haultfoeuille (2023). Graphon Estimation in bipartite graphs with observable edge labels and unobservable node labels. arXiv. 2304.03590. submitted. (link) (bib)
2022JournalArnak S. Dalalyan, Avetik Karagulyan, Lionel Riou-Durand (2022). Bounding the Error of Discretized Langevin Algorithms for Non-Strongly Log-Concave Targets. Journal of Machine Learning Research, 23(235), pp. 1–38. (link) (bib)
2022JournalArnak S. Dalalyan, Arshak Minasyan (2022). All-in-one robust estimator of the Gaussian mean. The Annals of Statistics, 50(2), pp. 1193 – 1219. (bib)
2022JournalTigran Galstyan, Arshak Minasyan, Arnak S. Dalalyan (2022). Optimal detection of the feature matching map in presence of noise and outliers. Electronic Journal of Statistics, 16(2), pp. 5720 – 5750. (link) (bib)
2022ConferenceLaura Tinsi and Arnak S. Dalalyan (2022). Risk bounds for aggregated shallow neural networks using Gaussian priors. In Conference on Learning Theory, July 2022, pp. 227–253. (link) (bib)
2021ConferenceNicolas Schreuder, Victor-Emmanuel Brunel, Arnak S. Dalalyan (2021). Statistical guarantees for generative models without domination. In Algorithmic Learning Theory, March 2021, pp. 1051–1071. (link) (bib)
2020JournalArnak S. Dalalyan (2020). Exponential weights in multivariate regression and a low-rankness favoring prior. Ann. Inst. H. Poincaré Probab. Statist., 56(2), pp. 1465-1483. (pdf) (bib)
2020JournalArnak S. Dalalyan, Lionel Riou-Durand (2020). On sampling from a log-concave density using kinetic Langevin diffusions. Bernoulli, 26(3), pp. 1956-1988. (link) (bib)
2020JournalAmir-Hossein Bateni, Arnak S. Dalalyan (2020). Confidence regions and minimax rates in outlier-robust estimation on the probability simplex. Electron. J. Statist., 14(2), pp. 2653–2677. (link) (bib)
2020ConferenceVictor-Emmanuel Brunel, Arnak S. Dalalyan, Nicolas Schreuder (2020). A nonasymptotic law of iterated logarithm for general M-estimators. In AISTATS 2020, pp. 1-8. (pdf) (bib)
2020ConferenceAvetik G. Karagulyan, Arnak S. Dalalyan (2020). Penalized Langevin dynamics with vanishing penalty for smooth and log-concave targets. In NeurIPS 2020, pp. 17594–17604. (link) (bib)
2019JournalArnak S. Dalalyan, Avetik Karagulyan (2019). User-friendly guarantees for the Langevin Monte Carlo with inaccurate gradient. Stoch. Proc. Appl., 129(12), pp. 5278-5311. (link) (bib)
2019JournalOlivier Collier, Arnak S. Dalalyan (2019). Rate-optimal estimation of p-dimensional linear functionals in a sparse Gaussian model. Electron. J. Statist., 13(2), pp. 2830-2864. (link) (bib)
2019ConferenceArnak S. Dalalyan, Philip Thompson (2019). Outlier-robust estimation of a sparse linear model using ell-1-penalized Huber's M-estimator. In Advances in Neural Information Processing Systems 32, pp. 13188–13198. (link) (bib)
2018JournalPierre C. Bellec, Arnak S. Dalalyan, Edwin Grappin, Quentin Paris (2018). On the prediction loss of the lasso in the partially labeled setting. Electron. J. Stat., 12(2), pp. 3443-3472. (link) (bib)
2018JournalArnak S. Dalalyan, Edwin Grappin, Quentin Paris (2018). On the Exponentially Weighted Aggregate with the Laplace Prior. Ann. Statist., 46(5), pp. 2452-2478. (link) (bib)
2018JournalArnak S. Dalalyan, Mehdi Sebbar (2018). Optimal Kullback-Leibler Aggregation in Mixture Density Estimation by Maximum Likelihood. Math. Stat. Learn., 1, pp. 1-35. (link) (bib)
2018JournalOlivier Collier, Arnak S. Dalalyan (2018). Estimating linear functionals of a sparse family of Poisson means. Statistical Inference for Stochastic Processes, 21(2), pp. 331-344. (link) (bib)
2018Technical reportPhilip Thompson, Arnak S. Dalalyan (2018). Restricted eigenvalue property for corrupted Gaussian designs. arXiv. 1805.08020. unpublished. (link) (bib)
2017JournalArnak S. Dalalyan, Mohamed Hebiri, Johannes Lederer (2017). On the Prediction Performance of the Lasso. Bernoulli, 23(1), pp. 552-581. (link) (bib)
2017JournalArnak S. Dalalyan (2017). Theoretical guarantees for approximate sampling from a smooth and log-concave density. J. R. Stat. Soc. B, 79, pp. 651–676. (pdf) (bib)
2017ConferenceArnak Dalalyan (2017). Further and stronger analogy between sampling and optimization: Langevin Monte Carlo and gradient descent. In Proceedings of the 2017 Conference on Learning Theory, pp. 678–689. (link) (bib)
2016JournalOlivier Collier, Arnak S. Dalalyan (2016). Minimax rates in permutation estimation for feature matching. Journal of Machine Learning Research, 17(6), pp. 1-32. (pdf) (bib)
2016JournalSamuel Balmand, Arnak S. Dalalyan (2016). On estimation of the diagonal elements of a sparse precision matrix. Electron. J. Stat., 10(1), pp. 1551–1579. (link) (bib)
2015JournalOlivier Collier, Arnak S. Dalalyan (2015). Curve registration by nonparametric goodness-of-fit testing. J. Statist. Plann. Inference, 162, pp. 20-42. (pdf) (bib)
2015JournalArnak S. Dalalyan (2015). Discussion on the paper: Hypotheses testing by convex optimization. Electron. J. Stat., 9(2), pp. 1733–1737. (pdf) (bib)
2015Technical reportSamuel Balmand, Arnak S. Dalalyan (2015). Convex programming approach to robust estimation of a multivariate Gaussian model. arXiv. 1512.04734. unpublished. (pdf) (bib)
2014JournalArnak S. Dalalyan, Yurii Ingster, Alexandre B. Tsybakov (2014). Statistical inference in compound functional models. Probab. Theory Related Fields, 158(3), pp. 512-532. (pdf) (bib)
2013JournalLaetitia Comminges, Arnak S. Dalalyan (2013). Minimax testing of a composite null hypothesis defined via a quadratic functional in the model of regression. Electron. J. Stat., 7, pp. 146–190. (link) (bib)
2013ConferenceArnak S. Dalalyan, Mohamed Hebiri, Katia Meziani, Joseph Salmon (2013). Learning Heteroscedastic Models by Convex Programming under Group Sparsity. In Journal of Machine Learning Research - W & CP 28(3) (ICML 2013), pp. 379–387. (pdf) (bib)
2013ConferenceOlivier Collier, Arnak S. Dalalyan (2013). Permutation estimation and minimax rates of identifiability. In Journal of Machine Learning Research - W & CP 31 (AI-STATS 2013), pp. 10-19. (pdf) (bib)
2012JournalJérome Courchay, Arnak S. Dalalyan, Renaud Keriven, Peter Sturm (2012). On Camera calibration with linear programming and loop constraint linearization. Int. J. Comput. Vis., 97(1), pp. 71–90. (pdf) (bib)
2012JournalArnak S. Dalalyan, Alexandre B. Tsybakov (2012). Sparse regression learning by aggregation and Langevin Monte-Carlo. J. Comput. System Sci., 78(5), pp. 1423–1443. (pdf) (bib)
2012JournalArnak S. Dalalyan, Renaud Keriven (2012). Robust estimation for an inverse problem arising in multiview geometry. J. Math. Imaging Vision, 43(1), pp. 10–23. (link) (bib)
2012JournalArnak S. Dalalyan, Alexandre B. Tsybakov (2012). Mirror averaging with sparsity priors. Bernoulli, 18(3), pp. 914–944. (pdf) (bib)
2012JournalArnak S. Dalalyan (2012). SOCP based variance free Dantzig Selector with application to robust estimation. C. R. Math. Acad. Sci. Paris, 350(15-16), pp. 785–788. (link) (bib)
2012JournalArnak S. Dalalyan, Joseph Salmon (2012). Sharp Oracle Inequalities for Aggregation of Affine Estimators. Ann. Statist., 40(4), pp. 2327–2355. (pdf) (bib)
2012JournalLa\"etitia Comminges, Arnak S. Dalalyan (2012). Tight conditions for consistency of variable selection in the context of high dimensionality. Ann. Statist, 40(5), pp. 2667-2696. (pdf) (bib)
2012ConferenceArnak S. Dalalyan and Olivier Collier (2012). Wilks' phenomenon and penalized likelihood-ratio test for nonparametric curve registration. In Journal of Machine Learning Research - Proceedings Track 22, pp. 264-272. (pdf) (bib)
2012ConferenceArnak S. Dalalyan, Yin Chen (2012). Fused sparsity and robust estimation for linear models with unknown variance. In Advances in Neural Information Processing Systems 25: NIPS, pp. 1268-1276. (pdf) (bib)
2011JournalArnak S. Dalalyan, Boris S. Nahapetian (2011). Description of random fields by means of one-point finite-conditional distributions. J. Contemp. Math. Anal., 46(2), pp. 113–119. (pdf) (bib)
2011JournalArnak S. Dalalyan, Nakahiro Yoshida (2011). Second-order asymptotic expansion for a non-synchronous covariation estimator. Ann. Inst. Henri Poincaré Probab. Stat., 47(3), pp. 748–789. (pdf) (bib)
2011ConferenceArnak S. Dalalyan and Joseph Salmon (2011). Competing against the Best Nearest Neighbor Filter in Regression. In Algorithmic Learning Theory - 22nd International Conference, ALT 2011, Espoo, Finland, October 5-7, 2011. Proceedings, pp. 129-143. (link) (bib)
2011ConferenceJoseph Salmon and Arnak S. Dalalyan (2011). Optimal aggregation of affine estimators. In Journal of Machine Learning Research - Proceedings Track 19, pp. 635-660. (pdf) (bib)
2011ConferenceCharles-Alban Deledalle, Joseph Salmon, Arnak S. Dalalyan (2011). Image denoising with patch based PCA: local versus global. In Proceedings of the British Machine Vision Conference, pp. 25.1–25.10. (link) (bib)
2011ConferenceLaetitia Comminges and Arnak S. Dalalyan (2011). Tight conditions for consistent variable selection in high dimensional nonparametric regression. In Journal of Machine Learning Research - Proceedings Track 19, pp. 187-206. (pdf) (bib)
2010ConferenceRégis Behmo and Paul Marcombes and Arnak S. Dalalyan and Véronique Prinet (2010). Towards Optimal Naive Bayes Nearest Neighbor. In Computer Vision - ECCV 2010, 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part IV, pp. 171-184. (link) (bib)
2010ConferenceJérome Courchay and Arnak S. Dalalyan and Renaud Keriven and Peter F. Sturm (2010). A global camera network calibration method with Linear Programming. In 3DPVT2010, pp. 1-8. (pdf) (bib)
2010ConferenceJérome Courchay and Arnak S. Dalalyan and Renaud Keriven and Peter F. Sturm (2010). Exploiting Loops in the Graph of Trifocal Tensors for Calibrating a Network of Cameras. In Computer Vision - ECCV 2010, 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II, pp. 85-99. (pdf) (bib)
2009ConferenceArnak S. Dalalyan, Renaud Keriven (2009). L_1-Penalized Robust Estimation for a Class of Inverse Problems Arising in Multiview Geometry. In Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, Vancouver, British Columbia, Canada, pp. 441-449. (pdf) (bib)
2009ConferenceArnak S. Dalalyan, Renaud Keriven (2009). Sparse learning approach to the problem of robust estimation of camera locations. In Computer Vision Workshops (ICCV Workshops), 2009 IEEE 12th International Conference on, pp. 436 -443. (pdf) (bib)
2009ConferenceArnak S. Dalalyan and Alexandre B. Tsybakov (2009). Sparse Regression Learning by Aggregation and Langevin Monte-Carlo. In COLT 2009 - The 22nd Conference on Learning Theory, Montreal, Quebec, Canada, June 18-21, 2009, pp. 1-10. (pdf) (bib)
2008JournalArnak S. Dalalyan and Anatoli Juditsky and Vladimir Spokoiny (2008). A New Algorithm for Estimating the Effective Dimension-Reduction Subspace. Journal of Machine Learning Research, 9, pp. 1647-1678. (pdf) (bib)
2008JournalArnak S. Dalalyan, Alexandre B. Tsybakov (2008). Aggregation by exponential weighting, sharp PAC-Bayesian bounds and sparsity. Machine Learning, 72(1-2), pp. 39-61. (pdf) (bib)
2007JournalArnak S. Dalalyan, Markus Rei\ss (2007). Asymptotic statistical equivalence for ergodic diffusions: the multidimensional case. Probab. Theory Related Fields, 137(1-2), pp. 25–47. (pdf) (bib)
2007JournalArnak S. Dalalyan (2007). Stein shrinkage and second-order efficiency for semiparametric estimation of the shift. Math. Methods Statist., 16(1), pp. 42–62. (pdf) (bib)
2007ConferenceArnak S. Dalalyan, Alexandre B. Tsybakov (2007). Aggregation by exponential weighting and sharp oracle inequalities. In Learning theory (COLT2007), Lecture Notes in Comput. Sci., Vol. 4539, pp. 97–111. (link) (bib)
2006JournalArnak S. Dalalyan, Markus Rei\ss (2006). Asymptotic statistical equivalence for scalar ergodic diffusions. Probab. Theory Related Fields, 134(2), pp. 248–282. (pdf) (bib)
2006JournalArnak S. Dalalyan, G. K. Golubev, Alexandre B. Tsybakov (2006). Penalized maximum likelihood and semiparametric second-order efficiency. Ann. Statist., 34(1), pp. 169–201. (link) (bib)
2005JournalArnak S. Dalalyan (2005). Sharp adaptive estimation of the drift function for ergodic diffusions. Ann. Statist., 33(6), pp. 2507–2528. (link) (bib)
2004JournalArnak S. Dalalyan, Yury A. Kutoyants (2004). On second order minimax estimation of invariant density for ergodic diffusion. Statist. Decisions, 22(1), pp. 17–41. (pdf) (bib)
2003JournalArnak S. Dalalyan, Yury A. Kutoyants (2003). Asymptotically efficient estimation of the derivative of the invariant density. Stat. Inference Stoch. Process., 6(1), pp. 89–107. (pdf) (bib)
2002JournalArnak S. Dalalyan, Yury A. Kutoyants (2002). Asymptotically efficient trend coefficient estimation for ergodic diffusion. Math. Methods Statist., 11(4), pp. 402–427 (2003). (pdf) (bib)
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Last update: May 29, 2015