Prof. Dr. Alexandra Carpentier

Prof. Dr. Alexandra Carpentier

Fakultät für Mathematik (FMA)
Institut für Mathematische Stochastik (IMST)
Universitätsplatz 2, 39106, Magdeburg, G18-408
Projekte

Aktuelle Projekte

Publikationen

2018

Artikel in Kongressband

Locatelli, Andrea;  Carpentier, Alexandra 

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); http://proceedings.mlr.press/v75/locatelli18a.html ; [Konferenz: 31st Annual Conference on Learning Theory, COLT 2018, Stockholm, 6-9 July 2018]

Locatelli, Andrea;  Carpentier, Alexandra;  Kpotufe, Samory 

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]

Begutachteter Zeitschriftenartikel

Carpentier, Alexandra;  Klopp, Olga;  Löffler, Matthias;  Nickl, Richard 

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; http://dx.doi.org/10.3150/17-BEJ933

Carpentier, Alexandra;  Kim, Arlene K. H. 

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; http://dx.doi.org/10.5705/ss.202016.0103

Blanchard, Gilles;  Carpentier, Alexandra;  Gutzeit, Maurilio 

Minimax euclidean separation rates for testing convex hypotheses in R d
In: Electronic journal of statistics: EJS - Ithaca, NY: Cornell University Library, Bd. 12.2018, 2, S. 3713-3735; http://dx.doi.org/10.1214/18-ejs1472

Buchbeitrag

Carpentier, Alexandra;  Klopp, Olga;  Löffler, Matthias 

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]

Nicht begutachteter Zeitschriftenartikel

Achdou, Juliette;  Lam, Joseph C.;  Carpentier, Alexandra;  Blanchard, Gilles 

A minimax near-optimal algorithm for adaptive rejection sampling
In: De.arxiv.org - [S.l.]: Arxiv.org, insges. 32 S., 2018; https://arxiv.org/abs/1810.09390

Carpentier, Alexandra;  Verzelen, Nicolas 

Adaptive estimation of the sparsity in the Gaussian vector model
In: De.arxiv.org - [S.l.]: Arxiv.org, insges. 76 S., 2018; https://arxiv.org/abs/1703.00167

Carpentier, Alexandra;  Delattre, Sylvain;  Roquain, Etienne;  Verzelen, Nicolas 

Estimating minimum effect with outlier selection
In: De.arxiv.org - [S.l.]: Arxiv.org, insges. 70 S., 2018; https://arxiv.org/abs/1809.08330

Carpentier, Alexandra;  Collier, Olivier;  Comminges, Laetitia;  Tsybakov, Alexandre B.;  Wang, Yuhao 

Minimax rate of testing in sparse linear regression
In: De.arxiv.org - [S.l.]: Arxiv.org, insges. 18 S., 2018; https://arxiv.org/abs/1804.06494

Carpentier, Alexandra;  Duval, Céline;  Mariucci, Ester 

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; https://arxiv.org/abs/1810.02998

2017

Artikel in Kongressband

Locatelli, Andrea;  Carpentier, Alexandra;  Kpotufe, Samory 

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]

Ghoshdastidar, Debarghya;  Gutzeit, Maurilio;  Carpentier, Alexandra;  Luxburg, Ulrike 

Two-sample tests for large random graphs using network statistics
In: Conference on Learning Theory: 7-10 July 2017, Amsterdam, Netherlands : [proceedings] - [Erscheinungsort nicht ermittelbar]: PMLR, S. 954-977 - (Proceedings of machine learning research; volume 65); proceedings.mlr.press/v65/ghoshdastidar17a.html ; [Konfernz: Conference on Learning Theory, Amsterdam, Netherlands, 7-10 July 2017]

Nicht begutachteter Zeitschriftenartikel

Locatelli, Andrea;  Carpentier, Alexandra;  Kpotufe, Samory 

Adaptivity to noise parameters in nonparametric active learning
In: De.arxiv.org - [S.l.]: Arxiv.org, insges. 32 S., 2017; https://arxiv.org/abs/1703.05841

Carpentier, Alexandra;  Kim, Arlene 

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; https://arxiv.org/abs/1502.04654

Ghoshdastidar, Debarghya;  Gutzeit, Maurilio;  Carpentier, Alexandra;  Luxenburg, Ulrike 

Two-sample tests for large random graphs using network statistics
In: De.arxiv.org - [S.l.]: Arxiv.org, insges. 24 S., 2017; https://arxiv.org/abs/1705.06168

2016

Artikel in Kongressband

Locatelli, Andrea;  Gutzeit, Maurilio;  Carpentier, Alexandra 

An optimal algorithm for the Thresholding Bandit Problem
In: International Conference on Machine Learning: 20-22 June 2016, New York, New York, USA : [proceedings] - [Erscheinungsort nicht ermittelbar]: PMLR, S. 1690-1698 - (Proceedings of machine learning research; volume 48); http://proceedings.mlr.press/v48/locatelli16.html ; [Konferenz: 33rd International Conference on Machine Learning, New York, 20-22 June 2016]

Locatelli, A.;  Gutzeit, M.;  Carpentier, A. 

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

Carpentier, Alexandra;  Schlüter, Teresa 

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]

Erraqabi, Akram;  Valko, Michal;  Carpentier, Alexandra;  Maillard, Odalric 

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); http://proceedings.mlr.press/v48/erraqabi16.html ; [Konferenz: 33rd International Conference on Machine Learning, New York, 20-22 June 2016]

Erraqabi, A.;  Valko, M.;  Carpentier, A.;  Maillard, O.-A. 

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

Carpentier, Alexandra;  Locatelli, Andrea 

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); http://proceedings.mlr.press/v49/carpentier16.html ; [Konferenz: 29th Conference on Learning Theory, COLT, New York, 23-26 June 2018]

2015

Artikel in Kongressband

Carpentier, A.;  Valko, M. 

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

Begutachteter Zeitschriftenartikel

Carpentier, A.;  Kim, A.K.H. 

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

Carpentier, A.;  Munos, R.;  Antosy, A. 

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

Carpentier, A. 

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

Carpentier, A.;  Nickl, R. 

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

Carpentier, A. 

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

2014

Artikel in Kongressband

Carpentier, A.;  Valko, M. 

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

Begutachteter Zeitschriftenartikel

Carpentier, A.;  Kim, A.K.H. 

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

Carpentier, A.;  Munos, R. 

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

2013

Artikel in Kongressband

Valko, M.;  Carpentier, A.;  Munos, R. 

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

Carpentier, A.;  Munos, R. 

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

Begutachteter Zeitschriftenartikel

Fruitet, J.;  Carpentier, A.;  Munos, R.;  Clerc, M. 

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

Carpentier, A. 

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

Thomas, E.;  Clerc, M.;  Carpentier, A.;  Daucea, E.;  Devlaminck, D.;  Munos, R. 

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

2012

Artikel in Kongressband

Carpentier, A.;  Munos, R. 

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

Fruitet, J.;  Carpentier, A.;  Munos, R.;  Clerc, M. 

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

Maillard, O.A.;  Carpentier, A. 

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

Begutachteter Zeitschriftenartikel

Carpentier, A.;  Munos, R. 

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

Carpentier, A.;  Munos, R. 

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

Buchbeitrag

Carpentier, Alexandra;  Munos, Rémi 

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); http://dx.doi.org/10.1007/978-3-642-34106-9_20 ; [Konferenz: 23rd International Conference on Algorithmic Learning Theory, ALT 2012, Lyon, France, October 29 - 31, 2012]

2011

Artikel in Kongressband

Carpentier, A.;  Munos, R. 

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

Carpentier, A.;  Maillard, O.-A.;  Munos, R. 

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

Begutachteter Zeitschriftenartikel

Carpentier, A.;  Lazaric, A.;  Ghavamzadeh, M.;  Munos, R.;  Auer, P. 

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

Lehrveranstaltungen

Wintersemester 2018/19

Mathematik des maschinellen Lernens: LSF

Seminar zur Statistik: LSF

Wahrscheinlichkeitstheorie: LSF  Elearning

  • Wahrscheinlichkeitstheorie (Übung): LSF
  • Wahrscheinlichkeitstheorie (Zusatzübung): LSF

Sommersemester 2018

Mathematik des Maschinellen Lernens II: LSF 

Modellierung 2 (FMA): LSF 

Oberseminar zur Stochastik: LSF 

Weiterführende Mathematische Statistik: LSF Elearning

  • Weiterführende Mathematische Statistik (Ü): LSF

Wintersemester 2017/18

Mathematik des maschinellen Lernens: LSF Elearning

Oberseminar zur Stochastik. LSF

Weiterführende Wahrscheinlichkeitstheorie: LSF Elearning

  • Weiterführende Wahrscheinlichkeitstheorie (Tutorium): LSF
  • Weiterführende Wahrscheinlichkeitstheorie (Übung): LSF

Letzte Änderung: 02.11.2018 - Ansprechpartner:

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