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2020
Confidence regions and minimax rates in outlier-robust estimation on the probability simplex
Electronic journal of statistics, vol. 14, iss. 2, pp. 2653-2677, 2020.
By A. -H. Bateni and A. S. Dalalyan@ARTICLE{Bateni20202653, author={Bateni, A.-H. and Dalalyan, A.S.}, title={Confidence regions and minimax rates in outlier-robust estimation on the probability simplex}, journal={Electronic Journal of Statistics}, year={2020}, volume={14}, number={2}, pages={2653-2677}, doi={10.1214/20-EJS1731}, note={cited
By 0}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088169633&doi=10.1214%2f20-EJS1731&partnerID=40&md5=fe9fb9cd08e5148bae142ae99b9217bd}, document_type={Article}, source={Scopus}, }On sampling from a log-concave density using kinetic langevin diffusions
Bernoulli, vol. 26, iss. 3, pp. 1956-1988, 2020.
By A. S. Dalalyan and L. Riou-Durand@ARTICLE{Dalalyan20201956, author={Dalalyan, A.S. and Riou-Durand, L.}, title={On sampling from a log-concave density using kinetic Langevin diffusions}, journal={Bernoulli}, year={2020}, volume={26}, number={3}, pages={1956-1988}, doi={10.3150/19-BEJ1178}, note={cited
By 0}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85091155335&doi=10.3150%2f19-BEJ1178&partnerID=40&md5=170cd248a1b45eb650ce382d250f1ca2}, document_type={Article}, source={Scopus}, }Exponential weights in multivariate regression and a low-rankness favoring prior
Annales de l'institut henri poincare (b) probability and statistics, vol. 56, iss. 2, pp. 1465-1483, 2020.
By A. S. Dalalyan@ARTICLE{Dalalyan20201465, author={Dalalyan, A.S.}, title={Exponential weights in multivariate regression and a low-rankness favoring prior}, journal={Annales de l'institut Henri Poincare (B) Probability and Statistics}, year={2020}, volume={56}, number={2}, pages={1465-1483}, doi={10.1214/19-AIHP1010}, note={cited
By 0}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082518536&doi=10.1214%2f19-AIHP1010&partnerID=40&md5=88723744a0472d1726f079dbaf4c47ea}, document_type={Article}, source={Scopus}, }A nonasymptotic law of iterated logarithm for general m-estimators
vol. 108, pp. 1331-1341, 2020.
By N. Schreuder, V. Brunel, and A. Dalalyan@ARTICLE{pmlr-v108-dalalyan20a, title= {A nonasymptotic law of iterated logarithm for general M-estimators}, author={Schreuder, Nicolas and Brunel, Victor-Emmanuel and Dalalyan, Arnak}, booktitle= {Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics}, pages= {1331-1341}, year= {2020}, editor= {Silvia Chiappa and Roberto Calandra}, volume= {108}, series= {Proceedings of Machine Learning Research}, month= {26-28 Aug}, publisher ={PMLR}, pdf= {http://proceedings.mlr.press/v108/dalalyan20a/dalalyan20a.pdf}, url= {http://proceedings.mlr.press/v108/dalalyan20a.html}, }
2019
Multidimensional linear functional estimation in sparse gaussian models and robust estimation of the mean
Electronic journal of statistics, , 2019.
By O. Collier and A. S. Dalalyan@article{collier:hal-01694889, author={Collier, Olivier and Dalalyan, Arnak S}, title={Multidimensional linear functional estimation in sparse Gaussian models and robust estimation of the mean}, journal={Electronic Journal of Statistics}, year={2019}, }
Multidimensional linear functional estimation in sparse gaussian models and robust estimation of the mean
Electronic journal of statistics, vol. 13, iss. 2, pp. 2830-2864, 2019.
By O. Collier and A. S. Dalalyan@ARTICLE{Collier20192830, author={Collier, O. and Dalalyan, A.S.}, title={Multidimensional linear functional estimation in sparse Gaussian models and robust estimation of the mean}, journal={Electronic Journal of Statistics}, year={2019}, volume={13}, number={2}, pages={2830-2864}, doi={10.1214/19-EJS1590}, note={cited
By 2}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85073359975&doi=10.1214%2f19-EJS1590&partnerID=40&md5=aedccb3278835c8bc811ca0df47b5984}, document_type={Article}, source={Scopus}, }User-friendly guarantees for the langevin monte carlo with inaccurate gradient
Stochastic processes and their applications, vol. 129, iss. 12, pp. 5278-5311, 2019.
By A. S. Dalalyan and A. Karagulyan@ARTICLE{Dalalyan20195278, author={Dalalyan, A.S. and Karagulyan, A.}, title={User-friendly guarantees for the Langevin Monte Carlo with inaccurate gradient}, journal={Stochastic Processes and their Applications}, year={2019}, volume={129}, number={12}, pages={5278-5311}, doi={10.1016/j.spa.2019.02.016}, note={cited
By 16}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062981328&doi=10.1016%2fj.spa.2019.02.016&partnerID=40&md5=ec48fdd466f9029a7bd9b2e7af8d979c}, document_type={Article}, source={Scopus}, }
2018
Estimating linear functionals of a sparse family of poisson means
Statistical inference for stochastic processes, , 2018.
By O. Collier and A. S. Dalalyan@article{collier:hal-01656605, author={Collier, Olivier and Dalalyan, Arnak S}, title={Estimating linear functionals of a sparse family of Poisson means}, journal={Statistical Inference for Stochastic Processes}, year={2018}, }
On the prediction loss of the lasso in the partially labeled setting
Electronic journal of statistics, vol. 12, iss. 2, pp. 3443-3472, 2018.
By P. C. Bellec, A. S. Dalalyan, E. Grappin, and Q. Paris@ARTICLE{Bellec20183443, author={Bellec, P.C. and Dalalyan, A.S. and Grappin, E. and Paris, Q.}, title={On the prediction loss of the lasso in the partially labeled setting}, journal={Electronic Journal of Statistics}, year={2018}, volume={12}, number={2}, pages={3443-3472}, doi={10.1214/18-EJS1457}, note={cited
By 2}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063375588&doi=10.1214%2f18-EJS1457&partnerID=40&md5=9bdab6eedcbae99bf9fbf0a7d604a57c}, document_type={Article}, source={Scopus}, }Estimating linear functionals of a sparse family of poisson means
Statistical inference for stochastic processes, vol. 21, iss. 2, pp. 331-344, 2018.
By O. Collier and A. S. Dalalyan@ARTICLE{Collier2018331, author={Collier, O. and Dalalyan, A.S.}, title={Estimating linear functionals of a sparse family of Poisson means}, journal={Statistical Inference for Stochastic Processes}, year={2018}, volume={21}, number={2}, pages={331-344}, doi={10.1007/s11203-018-9173-0}, note={cited
By 1}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85041505653&doi=10.1007%2fs11203-018-9173-0&partnerID=40&md5=2b05a012de069bfeab71d1312cd7cd08}, document_type={Article}, source={Scopus}, }On the exponentially weighted aggregate with the laplace prior
Annals of statistics, vol. 46, iss. 5, pp. 2452-2478, 2018.
By A. S. Dalalyan, E. Grappin, and Q. Paris@ARTICLE{Dalalyan20182452, author={Dalalyan, A.S. and Grappin, E. and Paris, Q.}, title={On the exponentially weighted aggregate with the laplace prior}, journal={Annals of Statistics}, year={2018}, volume={46}, number={5}, pages={2452-2478}, doi={10.1214/17-AOS1626}, note={cited
By 5}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85052610806&doi=10.1214%2f17-AOS1626&partnerID=40&md5=b2c02b889f4fa84d107838e03f2e7497}, document_type={Article}, source={Scopus}, }
2017
On the prediction performance of the lasso
Bernoulli, , 2017.
By A. Dalalyan, M. Hebiri, and J. C. Lederer@article{dalalyan:halshs-02599138, author={Dalalyan, Arnak and Hebiri, Mohamed and Lederer, Johannes C.}, title={On the prediction performance of the Lasso}, journal={Bernoulli}, year={2017}, }
On the prediction performance of the lasso
Bernoulli, , 2017.
By A. Dalalyan, M. Hebiri, and J. C. Lederer@article{dalalyan:halshs-02599138, author={Dalalyan, Arnak and Hebiri, Mohamed and Lederer, Johannes C.}, title={On the prediction performance of the Lasso}, journal={Bernoulli}, year={2017}, }
Theoretical guarantees for approximate sampling from smooth and log-concave densities
Journal of the royal statistical society. series b: statistical methodology, vol. 79, iss. 3, pp. 651-676, 2017.
By A. S. Dalalyan@ARTICLE{Dalalyan2017651, author={Dalalyan, A.S.}, title={Theoretical guarantees for approximate sampling from smooth and log-concave densities}, journal={Journal of the Royal Statistical Society. Series B: Statistical Methodology}, year={2017}, volume={79}, number={3}, pages={651-676}, doi={10.1111/rssb.12183}, note={cited
By 54}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85018851800&doi=10.1111%2frssb.12183&partnerID=40&md5=7c7fc831ab0b47fda13b16b46538cdaa}, document_type={Article}, source={Scopus}, }On the prediction performance of the lasso
Bernoulli, vol. 23, iss. 1, pp. 552-581, 2017.
By A. S. Dalalyan, M. Hebiri, and J. Lederer@ARTICLE{Dalalyan2017552, author={Dalalyan, A.S. and Hebiri, M. and Lederer, J.}, title={On the prediction performance of the Lasso}, journal={Bernoulli}, year={2017}, volume={23}, number={1}, pages={552-581}, doi={10.3150/15-BEJ756}, note={cited
By 42}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-84991786871&doi=10.3150%2f15-BEJ756&partnerID=40&md5=58154c2dae197087a07bbcbc9798eb03}, document_type={Article}, source={Scopus}, }
2016
On estimation of the diagonal elements of a sparse precision matrix
Electronic journal of statistics, vol. 10, iss. 1, pp. 1551-1579, 2016.
By S. Balmand and A. S. Dalalyan@ARTICLE{Balmand20161551, author={Balmand, S. and Dalalyan, A.S.}, title={On estimation of the diagonal elements of a sparse precision matrix}, journal={Electronic Journal of Statistics}, year={2016}, volume={10}, number={1}, pages={1551-1579}, doi={10.1214/16-EJS1148}, note={cited
By 3}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-84973351698&doi=10.1214%2f16-EJS1148&partnerID=40&md5=0d87b2626caf9d456d3e00d4eec252f7}, document_type={Article}, source={Scopus}, }Minimax rates in permutation estimation for feature matching
Journal of machine learning research, vol. 17, iss. None, p. -, 2016.
By O. Collier and A. S. Dalalyan@ARTICLE{Collier2016MinimaxMatching, author={Olivier Collier and Arnak S. Dalalyan}, title={Minimax rates in permutation estimation for feature matching}, journal={Journal of Machine Learning Research}, year={2016}, volume={17}, number={None}, pages={-}, }
Minimax rates in permutation estimation for feature matching
Journal of machine learning research, vol. 17, 2016.
By O. Collier and A. S. Dalalyan@ARTICLE{Collier2016, author={Collier, O. and Dalalyan, A.S.}, title={Minimax rates in permutation estimation for feature matching}, journal={Journal of Machine Learning Research}, year={2016}, volume={17}, note={cited
By 9}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-84962408596&partnerID=40&md5=b764c60aedeb371c5686be2acc2c6ad2}, document_type={Article}, source={Scopus}, }
2015
Curve registration by nonparametric goodness-of-fit testing
Journal of statistical planning and inference, vol. 162, pp. 20-42, 2015.
By O. Collier and A. S. Dalalyan@ARTICLE{Collier201520, author={Collier, O. and Dalalyan, A.S.}, title={Curve registration by nonparametric goodness-of-fit testing}, journal={Journal of Statistical Planning and Inference}, year={2015}, volume={162}, pages={20-42}, doi={10.1016/j.jspi.2015.02.004}, note={cited
By 6}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-84925292554&doi=10.1016%2fj.jspi.2015.02.004&partnerID=40&md5=7f1918c8e66e25898721c455473305b9}, document_type={Article}, source={Scopus}, }Discussion of -hypotheses testing by convex optimization-
Electronic journal of statistics, vol. 9, iss. 2, pp. 1733-1737, 2015.
By A. S. Dalalyan@ARTICLE{Dalalyan20151733, author={Dalalyan, A.S.}, title={Discussion of -hypotheses testing by convex optimization-}, journal={Electronic Journal of Statistics}, year={2015}, volume={9}, number={2}, pages={1733-1737}, doi={10.1214/15-EJS994}, note={cited
By 0}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-84939532993&doi=10.1214%2f15-EJS994&partnerID=40&md5=d6243b780fa7505f34726bd0be1ffc12}, document_type={Article}, source={Scopus}, }
2014
Statistical inference in compound functional models
Probability theory and related fields, vol. 158, iss. 3-4, pp. 513-532, 2014.
By A. Dalalyan, Y. Ingster, and A. B. Tsybakov@ARTICLE{Dalalyan2014513, author={Dalalyan, A. and Ingster, Y. and Tsybakov, A.B.}, title={Statistical inference in compound functional models}, journal={Probability Theory and Related Fields}, year={2014}, volume={158}, number={3-4}, pages={513-532}, doi={10.1007/s00440-013-0487-y}, note={cited
By 11}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-84897671636&doi=10.1007%2fs00440-013-0487-y&partnerID=40&md5=5fb8613c1c4e0a1501d0e72297fb4324}, document_type={Article}, source={Scopus}, }
2013
Learning heteroscedastic models by convex programming under group sparsity
Proceedings of the 30 th international conference on machine learning, , 2013.
By A. S. Dalalyan, M. Hebiri, K. Meziani, and J. Salmon@article{dalalyan:hal-00813908, author={Dalalyan, Arnak S. and Hebiri, Mohamed and Meziani, Katia and Salmon, Joseph}, title={Learning Heteroscedastic Models by Convex Programming under Group Sparsity}, journal={Proceedings of the 30 th International Conference on Machine Learning}, year={2013}, }
Permutation estimation and minimax matching thresholds
Journal of machine learning research, vol. 31, iss. None, pp. 10-19, 2013.
By O. Collier and A. Dalalyan@ARTICLE{Collier2013PermutationThresholds, author={Olivier Collier and Arnak Dalalyan}, title={Permutation estimation and minimax matching thresholds}, journal={Journal of Machine Learning Research}, year={2013}, volume={31}, number={None}, pages={10-19}, }
Permutation estimation and minimax matching thresholds
Journal of machine learning research, vol. 31, pp. 10-19, 2013.
By O. Collier and A. Dalalyan@ARTICLE{Collier201310, author={Collier, O. and Dalalyan, A.}, title={Permutation estimation and minimax matching thresholds}, journal={Journal of Machine Learning Research}, year={2013}, volume={31}, pages={10-19}, note={cited
By 1}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-84954235621&partnerID=40&md5=54d4279fe09db8ac95e2a6ea879eb925}, document_type={Conference Paper}, source={Scopus}, }Minimax testing of a composite null hypothesis defined via a quadratic functional in the model of regression
Electronic journal of statistics, vol. 7, iss. 1, pp. 146-190, 2013.
By L. Comminges and A. S. Dalalyan@ARTICLE{Comminges2013146, author={Comminges, L. and Dalalyan, A.S.}, title={Minimax testing of a composite null hypothesis defined via a quadratic functional in the model of regression}, journal={Electronic Journal of Statistics}, year={2013}, volume={7}, number={1}, pages={146-190}, doi={10.1214/13-EJS766}, note={cited
By 9}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-84873878429&doi=10.1214%2f13-EJS766&partnerID=40&md5=0e258063ccfa4d6f719dd9b0fe190e6d}, document_type={Article}, source={Scopus}, }
2012
Mirror averaging with sparsity priors
Bernoulli, , 2012.
By A. S. Dalalyan and A. Tsybakov@article{dalalyan:hal-00461580, author={Dalalyan, Arnak S. and Tsybakov, Alexandre}, title={Mirror averaging with sparsity priors}, journal={Bernoulli}, year={2012}, }
Sparse regression learning by aggregation and langevin monte-carlo
Journal of computer and system sciences, , 2012.
By A. S. Dalalyan and A. Tsybakov@article{dalalyan:hal-00362471, author={Dalalyan, Arnak S. and Tsybakov, Alexandre}, title={Sparse Regression Learning by Aggregation and Langevin Monte-Carlo}, journal={Journal of Computer and System Sciences}, year={2012}, }
Tight conditions for consistency of variable selection in the context of high dimensionality
Annals of statistics, vol. 40, iss. 5, pp. 2667-2696, 2012.
By L. Comminges and A. S. Dalalyan@ARTICLE{Comminges20122667, author={Comminges, L. and Dalalyan, A.S.}, title={Tight conditions for consistency of variable selection in the context of high dimensionality}, journal={Annals of Statistics}, year={2012}, volume={40}, number={5}, pages={2667-2696}, doi={10.1214/12-AOS1046}, note={cited
By 27}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-84873372742&doi=10.1214%2f12-AOS1046&partnerID=40&md5=5f2d89d14de23a8cfbf60c9c70e0a9a6}, document_type={Article}, source={Scopus}, }On camera calibration with linear programming and loop constraint linearization
International journal of computer vision, vol. 97, iss. 1, pp. 71-90, 2012.
By J. Courchay, A. S. Dalalyan, R. Keriven, and P. Sturm@ARTICLE{Courchay201271, author={Courchay, J. and Dalalyan, A.S. and Keriven, R. and Sturm, P.}, title={On camera calibration with linear programming and loop constraint linearization}, journal={International Journal of Computer Vision}, year={2012}, volume={97}, number={1}, pages={71-90}, doi={10.1007/s11263-011-0483-6}, note={cited
By 5}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-84859264313&doi=10.1007%2fs11263-011-0483-6&partnerID=40&md5=273c2ffb021daf5d4b5c2fc9d1bde2cd}, document_type={Article}, source={Scopus}, }Sparse regression learning by aggregation and langevin monte-carlo
Journal of computer and system sciences, vol. 78, iss. 5, pp. 1423-1443, 2012.
By A. S. Dalalyan and A. B. Tsybakov@ARTICLE{Dalalyan20121423, author={Dalalyan, A.S. and Tsybakov, A.B.}, title={Sparse regression learning by aggregation and Langevin Monte-Carlo}, journal={Journal of Computer and System Sciences}, year={2012}, volume={78}, number={5}, pages={1423-1443}, doi={10.1016/j.jcss.2011.12.023}, note={cited
By 43}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-84861604276&doi=10.1016%2fj.jcss.2011.12.023&partnerID=40&md5=62c67cdb5af94da9d8a4add7592ea9c6}, document_type={Conference Paper}, source={Scopus}, }Socp based variance free dantzig selector with application to robust estimation
Comptes rendus mathematique, vol. 350, iss. 15-16, pp. 785-788, 2012.
By A. S. Dalalyan@ARTICLE{Dalalyan2012785, author={Dalalyan, A.S.}, title={SOCP based variance free Dantzig Selector with application to robust estimation}, journal={Comptes Rendus Mathematique}, year={2012}, volume={350}, number={15-16}, pages={785-788}, doi={10.1016/j.crma.2012.09.016}, note={cited
By 5}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-84867329277&doi=10.1016%2fj.crma.2012.09.016&partnerID=40&md5=78ab3230a27ba094a2a44c51b6e7ee42}, document_type={Article}, source={Scopus}, }Mirror averaging with sparsity priors
Bernoulli, vol. 18, iss. 3, pp. 914-944, 2012.
By A. S. Dalalyan and A. B. Tsybakov@ARTICLE{Dalalyan2012914, author={Dalalyan, A.S. and Tsybakov, A.B.}, title={Mirror averaging with sparsity priors}, journal={Bernoulli}, year={2012}, volume={18}, number={3}, pages={914-944}, doi={10.3150/11-BEJ361}, note={cited
By 21}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-84871602377&doi=10.3150%2f11-BEJ361&partnerID=40&md5=6ce893aae1566e6d04ad0672cff36b2c}, document_type={Article}, source={Scopus}, }Robust estimation for an inverse problem arising in multiview geometry
Journal of mathematical imaging and vision, vol. 43, iss. 1, pp. 10-23, 2012.
By A. Dalalyan and R. Keriven@ARTICLE{Dalalyan201210, author={Dalalyan, A. and Keriven, R.}, title={Robust estimation for an inverse problem arising in multiview geometry}, journal={Journal of Mathematical Imaging and Vision}, year={2012}, volume={43}, number={1}, pages={10-23}, doi={10.1007/s10851-011-0281-3}, note={cited
By 7}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-84859420852&doi=10.1007%2fs10851-011-0281-3&partnerID=40&md5=f5b4c2a4567dc78c9a0656f1235145b7}, document_type={Review}, source={Scopus}, }Sharp oracle inequalities for aggregation of affine estimators
Annals of statistics, vol. 40, iss. 4, pp. 2327-2355, 2012.
By A. S. Dalalyan and J. Salmon@ARTICLE{Dalalyan20122327, author={Dalalyan, A.S. and Salmon, J.}, title={Sharp oracle inequalities for aggregation of affine estimators}, journal={Annals of Statistics}, year={2012}, volume={40}, number={4}, pages={2327-2355}, doi={10.1214/12-AOS1038}, note={cited
By 26}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-84884954887&doi=10.1214%2f12-AOS1038&partnerID=40&md5=4c1292bdc2a917a672f782ebb18cde6d}, document_type={Article}, source={Scopus}, }
2011
Tight conditions for consistent variable selection in high dimensional nonparametric regression
Journal of machine learning research, vol. 19, iss. None, pp. 187-205, 2011.
By L. Comminges and A. S. Dalalyan@ARTICLE{Comminges2011TightRegression, author={Laetitia Comminges and Arnak S. Dalalyan}, title={Tight conditions for consistent variable selection in high dimensional nonparametric regression}, journal={Journal of Machine Learning Research}, year={2011}, volume={19}, number={None}, pages={187-205}, }
Tight conditions for consistent variable selection in high dimensional nonparametric regression
Journal of machine learning research, vol. 19, pp. 187-205, 2011.
By L. Comminges and A. S. Dalalyan@ARTICLE{Comminges2011187, author={Comminges, L. and Dalalyan, A.S.}, title={Tight conditions for consistent variable selection in high dimensional nonparametric regression}, journal={Journal of Machine Learning Research}, year={2011}, volume={19}, pages={187-205}, note={cited
By 8}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-84873389494&partnerID=40&md5=599a178757ca5086dbdc54dba8e7e81f}, document_type={Conference Paper}, source={Scopus}, }Competing against the best nearest neighbor filter in regression
Lecture notes in computer science (including subseries lecture notes in artificial intelligence and lecture notes in bioinformatics), vol. 6925 LNAI, pp. 129-143, 2011.
By A. S. Dalalyan and J. Salmon@ARTICLE{Dalalyan2011129, author={Dalalyan, A.S. and Salmon, J.}, title={Competing against the best nearest neighbor filter in regression}, journal={Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, year={2011}, volume={6925 LNAI}, pages={129-143}, doi={10.1007/978-3-642-24412-4_13}, note={cited
By 1}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-80054093390&doi=10.1007%2f978-3-642-24412-4_13&partnerID=40&md5=b67055016739808aca5ca10ebf45bd97}, document_type={Conference Paper}, source={Scopus}, }Second-order asymptotic expansion for a non-synchronous covariation estimator
Annales de l'institut henri poincare (b) probability and statistics, vol. 47, iss. 3, pp. 748-789, 2011.
By A. Dalalyan and N. Yoshida@ARTICLE{Dalalyan2011748, author={Dalalyan, A. and Yoshida, N.}, title={Second-order asymptotic expansion for a non-synchronous covariation estimator}, journal={Annales de l'institut Henri Poincare (B) Probability and Statistics}, year={2011}, volume={47}, number={3}, pages={748-789}, doi={10.1214/10-AIHP383}, note={cited
By 8}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-79960165359&doi=10.1214%2f10-AIHP383&partnerID=40&md5=ba40bad55f6f86a1b1ea3cc9da2c112c}, document_type={Article}, source={Scopus}, }Description of random fields by means of one-point finite-conditional distributions
Journal of contemporary mathematical analysis, vol. 46, iss. 2, pp. 113-119, 2011.
By A. S. Dalalyan and B. S. Nahapetian@ARTICLE{Dalalyan2011113, author={Dalalyan, A.S. and Nahapetian, B.S.}, title={Description of random fields by means of one-point finite-conditional distributions}, journal={Journal of Contemporary Mathematical Analysis}, year={2011}, volume={46}, number={2}, pages={113-119}, doi={10.3103/S1068362311020075}, note={cited
By 0}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-79955669806&doi=10.3103%2fS1068362311020075&partnerID=40&md5=2fbffb6de535cb74e0d965fcd75c2d0f}, document_type={Article}, source={Scopus}, }Optimal aggregation of affine estimators
Journal of machine learning research, vol. 19, iss. None, pp. 635-660, 2011.
By J. Salmon and A. Dalalyan@ARTICLE{Salmon2011OptimalEstimators, author={Joseph Salmon and Arnak Dalalyan}, title={Optimal aggregation of affine estimators}, journal={Journal of Machine Learning Research}, year={2011}, volume={19}, number={None}, pages={635-660}, }
Optimal aggregation of affine estimators
Journal of machine learning research, vol. 19, pp. 635-660, 2011.
By J. Salmon and A. Dalalyan@ARTICLE{Salmon2011635, author={Salmon, J. and Dalalyan, A.}, title={Optimal aggregation of affine estimators}, journal={Journal of Machine Learning Research}, year={2011}, volume={19}, pages={635-660}, note={cited
By 3}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-84898450217&partnerID=40&md5=8e2abd3e1b381c00901c712afeb06e8e}, document_type={Conference Paper}, source={Scopus}, }
2010
Towards optimal naive bayes nearest neighbor
Lecture notes in computer science (including subseries lecture notes in artificial intelligence and lecture notes in bioinformatics), vol. 6314 LNCS, iss. PART 4, pp. 171-184, 2010.
By R. Behmo, P. Marcombes, A. Dalalyan, and V. Prinet@ARTICLE{Behmo2010171, author={Behmo, R. and Marcombes, P. and Dalalyan, A. and Prinet, V.}, title={Towards optimal naive bayes nearest neighbor}, journal={Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, year={2010}, volume={6314 LNCS}, number={PART 4}, pages={171-184}, doi={10.1007/978-3-642-15561-1_13}, note={cited
By 40}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-78149351842&doi=10.1007%2f978-3-642-15561-1_13&partnerID=40&md5=f2d63aa8651cc4c3e1657e3d388f42e7}, document_type={Conference Paper}, source={Scopus}, }Exploiting loops in the graph of trifocal tensors for calibrating a network of cameras
Lecture notes in computer science (including subseries lecture notes in artificial intelligence and lecture notes in bioinformatics), vol. 6312 LNCS, iss. PART 2, pp. 85-99, 2010.
By J. Courchay, A. Dalalyan, R. Keriven, and P. Sturm@ARTICLE{Courchay201085, author={Courchay, J. and Dalalyan, A. and Keriven, R. and Sturm, P.}, title={Exploiting loops in the graph of trifocal tensors for calibrating a network of cameras}, journal={Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, year={2010}, volume={6312 LNCS}, number={PART 2}, pages={85-99}, doi={10.1007/978-3-642-15552-9_7}, note={cited
By 5}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-78149352644&doi=10.1007%2f978-3-642-15552-9_7&partnerID=40&md5=812a741c83f57569ad1f620fd2ef7cd2}, document_type={Conference Paper}, source={Scopus}, }
2008
Aggregation by exponential weighting, sharp pac-bayesian bounds and sparsity
Machine learning, , 2008.
By A. S. Dalalyan and A. Tsybakov@article{dalalyan:hal-00265651, author={Dalalyan, Arnak S. and Tsybakov, Alexandre}, title={Aggregation by exponential weighting, sharp PAC-Bayesian bounds and sparsity}, journal={Machine Learning}, year={2008}, }
A new algorithm for estimating the effective dimension-reduction subspace
Journal of machine learning research, vol. 9, iss. None, pp. 1647-1678, 2008.
By A. S. Dalalyan, A. Juditsky, and V. Spokoiny@ARTICLE{Dalalyan2008ASubspace, author={Arnak S. Dalalyan and Anatoly Juditsky and Vladimir Spokoiny}, title={A new algorithm for estimating the effective dimension-reduction subspace}, journal={Journal of Machine Learning Research}, year={2008}, volume={9}, number={None}, pages={1647-1678}, }
A new algorithm for estimating the effective dimension-reduction subspace
Journal of machine learning research, vol. 9, pp. 1647-1678, 2008.
By A. S. Dalalyan, A. Juditsky, and V. Spokoiny@ARTICLE{Dalalyan20081647, author={Dalalyan, A.S. and Juditsky, A. and Spokoiny, V.}, title={A new algorithm for estimating the effective dimension-reduction subspace}, journal={Journal of Machine Learning Research}, year={2008}, volume={9}, pages={1647-1678}, note={cited
By 20}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-50949115024&partnerID=40&md5=63289e980d16039cc652c9a493a75198}, document_type={Article}, source={Scopus}, }Aggregation by exponential weighting, sharp pac-bayesian bounds and sparsity
Machine learning, vol. 72, iss. 1-2, pp. 39-61, 2008.
By A. Dalalyan and A. B. Tsybakov@ARTICLE{Dalalyan200839, author={Dalalyan, A. and Tsybakov, A.B.}, title={Aggregation by exponential weighting, sharp PAC-Bayesian bounds and sparsity}, journal={Machine Learning}, year={2008}, volume={72}, number={1-2}, pages={39-61}, doi={10.1007/s10994-008-5051-0}, note={cited
By 87}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-70350003059&doi=10.1007%2fs10994-008-5051-0&partnerID=40&md5=ba9105a1d855f79f8ef6e36206097ca8}, document_type={Article}, source={Scopus}, }
2007
Stein shrinkage and second-order efficiency for semiparametric estimation of the shift
Mathematical methods of statistics, vol. 16, iss. 1, pp. 42-62, 2007.
By A. S. Dalalyan@ARTICLE{Dalalyan200742, author={Dalalyan, A.S.}, title={Stein shrinkage and second-order efficiency for semiparametric estimation of the shift}, journal={Mathematical Methods of Statistics}, year={2007}, volume={16}, number={1}, pages={42-62}, doi={10.3103/S1066530707010048}, note={cited
By 6}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-47249146246&doi=10.3103%2fS1066530707010048&partnerID=40&md5=840b41be5c496bdf7b59be59d2d6c337}, document_type={Article}, source={Scopus}, }Aggregation by exponential weighting and sharp oracle inequalities
Lecture notes in computer science (including subseries lecture notes in artificial intelligence and lecture notes in bioinformatics), vol. 4539 LNAI, pp. 97-111, 2007.
By A. S. Dalalyan and A. B. Tsybakov@ARTICLE{Dalalyan200797, author={Dalalyan, A.S. and Tsybakov, A.B.}, title={Aggregation by exponential weighting and sharp oracle inequalities}, journal={Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, year={2007}, volume={4539 LNAI}, pages={97-111}, doi={10.1007/978-3-540-72927-3_9}, note={cited
By 57}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-38049046503&doi=10.1007%2f978-3-540-72927-3_9&partnerID=40&md5=e66c7086015356b4b2ea9c225c35d7cb}, document_type={Conference Paper}, source={Scopus}, }Asymptotic statistical equivalence for ergodic diffusions: the multidimensional case
Probability theory and related fields, vol. 137, iss. 1-2, pp. 25-47, 2007.
By A. Dalalyan and M. Reiß@ARTICLE{Dalalyan200725, author={Dalalyan, A. and Reiß, M.}, title={Asymptotic statistical equivalence for ergodic diffusions: The multidimensional case}, journal={Probability Theory and Related Fields}, year={2007}, volume={137}, number={1-2}, pages={25-47}, doi={10.1007/s00440-006-0502-7}, note={cited
By 20}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-33846867045&doi=10.1007%2fs00440-006-0502-7&partnerID=40&md5=747fabf7ebfa67a71858906e393a8b2e}, document_type={Review}, source={Scopus}, }
2006
Asymptotic statistical equivalence for scalar ergodic diffusions
Probability theory and related fields, vol. 134, iss. 2, pp. 248-282, 2006.
By A. Dalalyan and M. Reiß@ARTICLE{Dalalyan2006248, author={Dalalyan, A. and Reiß, M.}, title={Asymptotic statistical equivalence for scalar ergodic diffusions}, journal={Probability Theory and Related Fields}, year={2006}, volume={134}, number={2}, pages={248-282}, doi={10.1007/s00440-004-0416-1}, note={cited
By 16}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-28644440536&doi=10.1007%2fs00440-004-0416-1&partnerID=40&md5=be072a1aafad1c97b056f147a8029052}, document_type={Article}, source={Scopus}, }Penalized maximum likelihood and semiparametric second-order efficiency
Annals of statistics, vol. 34, iss. 1, pp. 169-201, 2006.
By A. S. Dalalyan, G. K. Golubev, and A. B. Tsybakov@ARTICLE{Dalalyan2006169, author={Dalalyan, A.S. and Golubev, G.K. and Tsybakov, A.B.}, title={Penalized maximum likelihood and semiparametric second-order efficiency}, journal={Annals of Statistics}, year={2006}, volume={34}, number={1}, pages={169-201}, doi={10.1214/009053605000000895}, note={cited
By 27}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-33744800008&doi=10.1214%2f009053605000000895&partnerID=40&md5=eb3e1e2fe01788274be43ada48822547}, document_type={Article}, source={Scopus}, }
2005
Sharp adaptive estimation of the drift function for ergodic diffusions
Annals of statistics, vol. 33, iss. 6, pp. 2507-2528, 2005.
By A. Dalalyan@ARTICLE{Dalalyan20052507, author={Dalalyan, A.}, title={Sharp adaptive estimation of the drift function for ergodic diffusions}, journal={Annals of Statistics}, year={2005}, volume={33}, number={6}, pages={2507-2528}, doi={10.1214/009053605000000615}, note={cited
By 20}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-33644900974&doi=10.1214%2f009053605000000615&partnerID=40&md5=3abf9e131934da96ac9d278789e550cb}, document_type={Article}, source={Scopus}, }