Alexandre B. Tsybakov

According to our database1, Alexandre B. Tsybakov authored at least 26 papers between 1992 and 2022.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2022
Improved Clustering Algorithms for the Bipartite Stochastic Block Model.
IEEE Trans. Inf. Theory, 2022

Benign overfitting and adaptive nonparametric regression.
CoRR, 2022

A gradient estimator via L1-randomization for online zero-order optimization with two point feedback.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Distributed Zero-Order Optimization under Adversarial Noise.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
Optimal Variable Selection and Adaptive Noisy Compressed Sensing.
IEEE Trans. Inf. Theory, 2020

Exploiting Higher Order Smoothness in Derivative-free Optimization and Continuous Bandits.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019
Algorithms of Robust Stochastic Optimization Based on Mirror Descent Method.
Autom. Remote. Control., 2019

Minimax Rate of Testing in Sparse Linear Regression.
Autom. Remote. Control., 2019

Does data interpolation contradict statistical optimality?
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2015
Estimation of matrices with row sparsity.
Probl. Inf. Transm., 2015

Sharp oracle bounds for monotone and convex regression through aggregation.
J. Mach. Learn. Res., 2015

2013
Empirical Entropy, Minimax Regret and Minimax Risk.
CoRR, 2013

Pivotal Estimation in High-Dimensional Regression via Linear Programming.
Proceedings of the Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik, 2013

2012
On Walsh code assignment.
Probl. Inf. Transm., 2012

Sparse regression learning by aggregation and Langevin Monte-Carlo.
J. Comput. Syst. Sci., 2012

2009
Taking Advantage of Sparsity in Multi-Task Learning.
Proceedings of the COLT 2009, 2009

Introduction to Nonparametric Estimation.
Springer series in statistics, Springer, ISBN: 978-0-387-79052-7, 2009

2008
Aggregation by exponential weighting, sharp PAC-Bayesian bounds and sparsity.
Mach. Learn., 2008

2007
Aggregation by Exponential Weighting and Sharp Oracle Inequalities.
Proceedings of the Learning Theory, 20th Annual Conference on Learning Theory, 2007

Sparse Density Estimation with <i>l</i><sub>1</sub> Penalties.
Proceedings of the Learning Theory, 20th Annual Conference on Learning Theory, 2007

2006
Remark on "Recursive Aggregation of Estimators by the Mirror Descent Algorithm with Averaging" published in <i>Probl. Peredachi Inf.</i>, 2005, no. 4.
Probl. Inf. Transm., 2006

Aggregation and Sparsity Via <i>l</i><sub>1</sub> Penalized Least Squares.
Proceedings of the Learning Theory, 19th Annual Conference on Learning Theory, 2006

2005
Recursive Aggregation of Estimators by the Mirror Descent Algorithm with Averaging.
Probl. Inf. Transm., 2005

Generalization Error Bounds for Aggregation by Mirror Descent with Averaging.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

2003
Optimal Rates of Aggregation.
Proceedings of the Computational Learning Theory and Kernel Machines, 2003

1992
Optimal and robust kernel algorithms for passive stochastic approximation.
IEEE Trans. Inf. Theory, 1992


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