FACULTY OF

MATHEMATICS

A minimax near-optimal algorithm for adaptive rejection sampling
In: Algorithmic Learning Theory - PMLR; Garivier, Aurélien, S. 94-126, 2019 - (Proceedings of Machine Learning Research; 98) ; [Konferenz: 30th International Conference on Algorithmic Learning Theory, Chicago, Illinois, 22-24 March 2019]

Active multiple matrix completion with adaptive confidence sets
In: The 22nd International Conference on Artificial Intelligence and Statistics - PMLR; Chaudhuri, Kamalika, S. 1783-1791, 2019 - (Proceedings of Machine Learning Research; 89) ; [Konferenz: 22nd International Conference on Artificial Intelligence and Statistics, Naha, Okinawa, Japan, 16-18 April 2019]

Rotting bandits are no harder than stochastic ones
In: The 22nd International Conference on Artificial Intelligence and Statistics - PMLR; Chaudhuri, Kamalika, S. 2564-2572, 2019 - (Proceedings of Machine Learning Research; 89) ; [Konferenz: 22nd International Conference on Artificial Intelligence and Statistics, Naha, Okinawa, Japan, 16-18 April 2019]

Adaptive estimation of the sparsity in the Gaussian vector model
In: The annals of statistics - Hayward, Calif.: IMS Business Off., Bd. 47.2019, 1, S. 93-126

Minimax rate of testing in sparse linear regression
In: Automation and remote control - Dordrecht [u.a.]: Springer Science + Business Media B.V, Bd. 80.2019, 10, S. 1817-1834

Topics in statistical minimax hypothesis testing
In: Magdeburg, 2019, 99 Seiten, 1 Diagramm, 30 cm ; [Literaturverzeichnis: Seite 95-99]

Local minimax rates for closeness testing of discrete distributions
In: De.arxiv.org - [S.l.]: Arxiv.org, 2019, article 1902.01219, insgesamt 62 Seiten

Optimal sparsity testing in linear regression model
In: De.arxiv.org - [S.l.]: Arxiv.org, 2019, Artikel 1901.08802, insgesamt 50 Seiten

Restless dependent bandits with fading memory
In: De.arxiv.org - [S.l.]: Arxiv.org, 2019, article 1906.10454, insgesamt 30 Seiten

Two-sample hypothesis testing for inhomogeneous random graphs
In: De.arxiv.org - [S.l.]: Arxiv.org, 2019, article 1707.00833, insgesamt 54 Seiten

Adaptivity to smoothness in X-armed bandits
In: Conference on Learning Theory: 6-9 July 2018 : [proceedings] - [Erscheinungsort nicht ermittelbar]: PMLR, S. 1463-1492 - (Proceedings of machine learning research; volume 75)

An adaptive strategy for active learning with smooth decision boundary
In: Algorithmic Learning Theory 2018: 7-9 April 2018 : [proceedings] - [Erscheinungsort nicht ermittelbar]: PMLR, S. 547-571; proceedings.mlr.press/v83/locatelli18a.html ; [Konferenz: Algorithmic Learning Theory 2018, Lanzarote, Spain, 7-9 April 2018]

Adaptive confidence sets for matrix completion
In: Bernoulli: official journal of the Bernoulli Society for Mathematical Statistics and Probability - Aarhus, Vol. 24.2018, 4A, S. 2429-2460

An iterative hard thresholding estimator for low rank matrix recovery with explicit limiting distribution
In: Statistica Sinica - Taipei: Statistica Sinica, Institute of Statistical Science, Academia Sinica, Bd. 28.2018, 3, S. 1371-1393

Minimax euclidean separation rates for testing convex hypotheses in R d
In: Electronic journal of statistics - Ithaca, NY: Cornell University Library, Bd. 12.2018, 2, S. 3713-3735

Constructing confidence sets for the matrix completion problem
In: Nonparametric statistics: 3nd ISNPS, Avignon, France, June 2016 - Cham: Springer International Publishing, 2018 ; [Konferenz: 3rd Conference of the International Society for Nonparametric Statistics, ISNPS, Avignon, France, June 11-16, 2016]

A minimax near-optimal algorithm for adaptive rejection sampling
In: De.arxiv.org - [S.l.]: Arxiv.org, insges. 32 S., 2018

Adaptive estimation of the sparsity in the Gaussian vector model
In: De.arxiv.org - [S.l.]: Arxiv.org, insges. 76 S., 2018

Estimating minimum effect with outlier selection
In: De.arxiv.org - [S.l.]: Arxiv.org, insges. 70 S., 2018

Minimax rate of testing in sparse linear regression
In: De.arxiv.org - [S.l.]: Arxiv.org, insges. 18 S., 2018

Total variation distance for discretely observed Lévy processes : a Gaussian approximation of the small jumps
In: De.arxiv.org - [S.l.]: Arxiv.org, insges. 32 S., 2018

Adaptivity to noise parameters in nonparametric active learning
In: Conference on Learning Theory: 7-10 July 2017, Amsterdam, Netherlands : [proceedings] - [Erscheinungsort nicht ermittelbar]: PMLR, S. 1383-1416 - (Proceedings of machine learning research; volume 65); proceedings.mlr.press/v65/locatelli-andrea17a.html ; [Konfernz: Conference on Learning Theory, Amsterdam, Netherlands, 7-10 July 2017]

Two-sample tests for large random graphs using network statistics
In: Conference on Learning Theory - [Erscheinungsort nicht ermittelbar]: PMLR, S. 954-977, 2017 - (Proceedings of machine learning research; volume 65) ; [Konfernz: Conference on Learning Theory, Amsterdam, Netherlands, 7-10 July 2017]

Adaptivity to noise parameters in nonparametric active learning
In: De.arxiv.org - [S.l.]: Arxiv.org, insges. 32 S., 2017

An iterative hard thresholding estimator for low rank matrix recovery with explicit limiting distribution
In: De.arxiv.org - [S.l.]: Arxiv.org, insges. 40 S., 2017

Two-sample tests for large random graphs using network statistics
In: De.arxiv.org - [S.l.]: Arxiv.org, insges. 24 S., 2017

An optimal algorithm for the Thresholding Bandit Problem
In: International Conference on Machine Learning - [Erscheinungsort nicht ermittelbar]: PMLR, S. 1690-1698, 2016 - (Proceedings of machine learning research; volume 48) ; [Konferenz: 33rd International Conference on Machine Learning, New York, 20-22 June 2016]

An optimal algorithm for the thresholding bandit problem
In: In: 33rd International Conference on Machine Learning, ICML 2016, Bd. 4, S. 2539-2554, 2016

Learning relationships between data obtained independently
In: Artificial Intelligence and Statistics: 9-11 May 2016, Cadiz, Spain : [proceedings] - [Erscheinungsort nicht ermittelbar]: PMLR, S. 658-666 - (Proceedings of machine learning research; volume 51); proceedings.mlr.press/v51/carpentier16b.html ; [Konferenz: 19th International Conference on Artificial Intelligence and Statistics, Cadiz, Spain, 9-11 May 2016]

Pliable rejection sampling
In: International Conference on Machine Learning: 20-22 June 2016, New York, New York, USA : [proceedings] - [Erscheinungsort nicht ermittelbar]: PMLR, S. 21-21-2129 - (Proceedings of machine learning research; volume 48)

Pliable rejection sampling
In: In: 33rd International Conference on Machine Learning, ICML 2016, Bd. 5, S. 3122-3137, 2016

Tight (lower) bounds for the fixed budget best arm identification bandit problem
In: Conference on Learning Theory: 23-26 June 2018, Columbia University, New York, New York, USA : [proceedings] - [Erscheinungsort nicht ermittelbar]: PMLR, S. 590-604, 2016 - (Proceedings of machine learning research; volume 49)

Simple regret for infinitely many armed bandits
In: In: 32nd International Conference on Machine Learning, ICML 2015, Bd. 2, S. 1133-1141, 2015

Adaptive and minimax optimal estimation of the tail coefficient
In: In: Statistica Sinica, Bd. 25, 3, S. 1133-1144, 2015

Adaptive strategy for stratified Monte Carlo sampling
In: In: Journal of Machine Learning Research, Bd. 16, S. 2231-2271, 2015

Implementable confidence sets in high dimensional regression
In: In: Journal of Machine Learning Research, Bd. 38, S. 120-128, 2015

On signal detection and confidence sets for low rank inference problems
In: In: Electronic Journal of Statistics, Bd. 9, 2, S. 2675-2688, 2015

Testing the regularity of a smooth signal
In: In: Bernoulli, Bd. 21, 1, S. 465-488, 2015

Extreme bandits
In: In: Advances in Neural Information Processing Systems, Bd. 2, January, S. 1089-1097, 2014

Adaptive confidence intervals for the tail coefficient in a wide second order class of Pareto models
In: In: Electronic Journal of Statistics, 1, S. 2066-2110, 2014

Minimax number of strata for online stratified sampling: The case of noisy samples
In: In: Theoretical Computer Science, Bd. 558, C, S. 77-106, 2014

Stochastic simultaneous optimistic optimization
In: In: 30th International Conference on Machine Learning, ICML 2013, PART 1, S. 678-686, 2013

Toward optimal stratification for stratified Monte-Carlo integration
In: In: 30th International Conference on Machine Learning, ICML 2013, PART 1, S. 687-695, 2013

Automatic motor task selection via a bandit algorithm for a brain-controlled button
In: In: Journal of Neural Engineering, Bd. 10, 1, 2013

Honest and adaptive confidence sets in Lp
In: In: Electronic Journal of Statistics, Bd. 7, 1, S. 2875-2923, 2013

Optimizing P300-speller sequences by RIP-ping groups apart
In: In: International IEEE/EMBS Conference on Neural Engineering, NER, S. 1062-1065, 2013

Adaptive stratified sampling for Monte-Carlo integration of differentiable functions
In: In: Advances in Neural Information Processing Systems, Bd. 1, S. 251-259, 2012

Bandit algorithms boost motor-task selection for brain computer interfaces
In: In: Advances in Neural Information Processing Systems, Bd. 1, S. 449-457, 2012

Online allocation and homogeneous partitioning for piecewise constant mean-approximation
In: In: Advances in Neural Information Processing Systems, Bd. 3, S. 1961-1969, 2012

Bandit Theory meets Compressed Sensing for high-dimensional Stochastic Linear Bandit
In: In: Journal of Machine Learning Research, Bd. 22, S. 190-198, 2012

Minimax number of strata for online stratified sampling given noisy samples
In: In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bd. 7568 LNAI, S. 229-244, 2012

Minimax number of strata for online stratified sampling given noisy samples
In: Algorithmic learning theory: 23rd international conference, ALT 2012, Lyon, France, October 29 - 31, 2012 ; proceedings - Berlin [u.a.]: Springer, S. 229-244 - (Lecture notes in computer science; 7568)

Finite-time analysis of stratified sampling for Monte Carlo
In: In: Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011, 2011

Sparse recovery with Brownian sensing
In: In: Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011, 2011

Upper-confidence-bound algorithms for active learning in multi-armed bandits
In: In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bd. 6925 LNAI, S. 189-203, 2011