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2020 – today
- 2023
[c56]Sasila Ilandarideva, Yannis Bekri, Anatoli Iouditski, Vianney Perchet:
Stochastic Mirror Descent for Large-Scale Sparse Recovery. AISTATS 2023: 5931-5957- [c55]Côme Fiegel, Pierre Ménard, Tadashi Kozuno, Rémi Munos, Vianney Perchet, Michal Valko:
Adapting to game trees in zero-sum imperfect information games. ICML 2023: 10093-10135 - [c54]Nadav Merlis, Hugo Richard, Flore Sentenac, Corentin Odic, Mathieu Molina, Vianney Perchet:
On Preemption and Learning in Stochastic Scheduling. ICML 2023: 24478-24516 - [i71]Ziyad Benomar, Evgenii Chzhen, Nicolas Schreuder, Vianney Perchet:
Addressing bias in online selection with limited budget of comparisons. CoRR abs/2303.09205 (2023) - [i70]Hugo Richard, Etienne Boursier, Vianney Perchet:
Constant or logarithmic regret in asynchronous multiplayer bandits. CoRR abs/2305.19691 (2023) - [i69]Felipe Garrido-Lucero, Benjamin Heymann, Maxime Vono, Patrick Loiseau, Vianney Perchet:
DU-Shapley: A Shapley Value Proxy for Efficient Dataset Valuation. CoRR abs/2306.02071 (2023) - [i68]Flore Sentenac, Nathan Noiry, Matthieu Lerasle, Laurent Ménard, Vianney Perchet:
Online Matching in Geometric Random Graphs. CoRR abs/2306.07891 (2023) - [i67]Mathieu Molina, Nicolas Gast, Patrick Loiseau, Vianney Perchet:
Trading-off price for data quality to achieve fair online allocation. CoRR abs/2306.13440 (2023) - [i66]Côme Fiegel, Pierre Ménard, Tadashi Kozuno, Rémi Munos, Vianney Perchet, Michal Valko:
Local and adaptive mirror descents in extensive-form games. CoRR abs/2309.00656 (2023) - 2022
- [j11]Thomas Nedelec, Clément Calauzènes, Noureddine El Karoui, Vianney Perchet:
Learning in Repeated Auctions. Found. Trends Mach. Learn. 15(3): 176-334 (2022) - [j10]Thomas Nedelec
, Clément Calauzènes, Vianney Perchet, Noureddine El Karoui:
Revenue-Maximizing Auctions: A Bidder's Standpoint. Oper. Res. 70(5): 2767-2783 (2022) - [c53]Evrard Garcelon, Matteo Pirotta, Vianney Perchet:
Encrypted Linear Contextual Bandit. AISTATS 2022: 2519-2551 - [c52]Etienne Boursier, Vianney Perchet, Marco Scarsini:
Social Learning in Non-Stationary Environments. ALT 2022: 128-129 - [c51]Evrard Garcelon, Kamalika Chaudhuri, Vianney Perchet, Matteo Pirotta:
Privacy Amplification via Shuffling for Linear Contextual Bandits. ALT 2022: 381-407 - [c50]Vivien Cabannes, Francis R. Bach, Vianney Perchet, Alessandro Rudi:
Active Labeling: Streaming Stochastic Gradients. NeurIPS 2022 - [c49]Vianney Perchet, Philippe Rigollet, Thibaut Le Gouic:
An Algorithmic Solution to the Blotto Game using Multi-marginal Couplings. EC 2022: 208-209 - [i65]Vianney Perchet, Philippe Rigollet, Thibaut Le Gouic:
An algorithmic solution to the Blotto game using multi-marginal couplings. CoRR abs/2202.07318 (2022) - [i64]Vivien Cabannes, Francis R. Bach, Vianney Perchet, Alessandro Rudi:
Active Labeling: Streaming Stochastic Gradients. CoRR abs/2205.13255 (2022) - [i63]Hugo Richard, Flore Sentenac, Corentin Odic, Mathieu Molina, Vianney Perchet:
Static Scheduling with Predictions Learned through Efficient Exploration. CoRR abs/2205.15695 (2022) - [i62]Sasila Ilandarideva, Yannis Bekri, Anatoli B. Juditsky, Vianney Perchet:
Stochastic Mirror Descent for Large-Scale Sparse Recovery. CoRR abs/2210.12882 (2022) - [i61]Etienne Boursier, Vianney Perchet:
A survey on multi-player bandits. CoRR abs/2211.16275 (2022) - [i60]Côme Fiegel, Pierre Ménard, Tadashi Kozuno, Rémi Munos, Vianney Perchet, Michal Valko:
Adapting to game trees in zero-sum imperfect information games. CoRR abs/2212.12567 (2022) - 2021
- [c48]Thomas Nedelec, Jules Baudet, Vianney Perchet, Noureddine El Karoui:
Adversarial Learning in Revenue-Maximizing Auctions. AAMAS 2021: 955-963 - [c47]Xavier Fontaine, Pierre Perrault, Michal Valko, Vianney Perchet:
Online A-Optimal Design and Active Linear Regression. ICML 2021: 3374-3383 - [c46]Flore Sentenac, Jialin Yi, Clément Calauzènes, Vianney Perchet, Milan Vojnovic:
Pure Exploration and Regret Minimization in Matching Bandits. ICML 2021: 9434-9442 - [c45]Nicolò Cesa-Bianchi, Tommaso Cesari, Yishay Mansour, Vianney Perchet:
A New Theoretical Framework for Fast and Accurate Online Decision-Making. NeurIPS 2021: 9152-9166 - [c44]Evrard Garcelon, Vianney Perchet, Ciara Pike-Burke, Matteo Pirotta:
Local Differential Privacy for Regret Minimization in Reinforcement Learning. NeurIPS 2021: 10561-10573 - [c43]Etienne Boursier, Tristan Garrec, Vianney Perchet, Marco Scarsini:
Making the most of your day: online learning for optimal allocation of time. NeurIPS 2021: 11208-11219 - [c42]Flore Sentenac, Etienne Boursier, Vianney Perchet:
Decentralized Learning in Online Queuing Systems. NeurIPS 2021: 18501-18512 - [c41]Reda Ouhamma, Odalric-Ambrym Maillard, Vianney Perchet:
Online Sign Identification: Minimization of the Number of Errors in Thresholding Bandits. NeurIPS 2021: 18577-18589 - [c40]Nathan Noiry, Vianney Perchet, Flore Sentenac:
Online Matching in Sparse Random Graphs: Non-Asymptotic Performances of Greedy Algorithm. NeurIPS 2021: 21400-21412 - [c39]Reda Ouhamma, Odalric-Ambrym Maillard, Vianney Perchet:
Stochastic Online Linear Regression: the Forward Algorithm to Replace Ridge. NeurIPS 2021: 24430-24441 - [i59]Matthieu Jedor, Jonathan Louëdec, Vianney Perchet:
Be Greedy in Multi-Armed Bandits. CoRR abs/2101.01086 (2021) - [i58]Etienne Boursier, Tristan Garrec, Vianney Perchet, Marco Scarsini:
Making the most of your day: online learning for optimal allocation of time. CoRR abs/2102.08087 (2021) - [i57]Evrard Garcelon, Vianney Perchet, Matteo Pirotta:
Homomorphically Encrypted Linear Contextual Bandit. CoRR abs/2103.09927 (2021) - [i56]Firas Jarboui, Vianney Perchet:
A Generalised Inverse Reinforcement Learning Framework. CoRR abs/2105.11812 (2021) - [i55]Flore Sentenac, Etienne Boursier, Vianney Perchet:
Decentralized Learning in Online Queuing Systems. CoRR abs/2106.04228 (2021) - [i54]Firas Jarboui, Vianney Perchet:
Quickest change detection with unknown parameters: Constant complexity and near optimality. CoRR abs/2106.05061 (2021) - [i53]Firas Jarboui, Vianney Perchet:
Offline Inverse Reinforcement Learning. CoRR abs/2106.05068 (2021) - [i52]Firas Jarboui, Vianney Perchet:
Unsupervised Neural Hidden Markov Models with a Continuous latent state space. CoRR abs/2106.06536 (2021) - [i51]Nathan Noiry, Flore Sentenac, Vianney Perchet:
Online Matching in Sparse Random Graphs: Non-Asymptotic Performances of Greedy Algorithm. CoRR abs/2107.00995 (2021) - [i50]Flore Sentenac, Jialin Yi, Clément Calauzènes, Vianney Perchet, Milan Vojnovic:
Pure Exploration and Regret Minimization in Matching Bandits. CoRR abs/2108.00230 (2021) - [i49]Reda Ouhamma, Rémy Degenne, Pierre Gaillard, Vianney Perchet:
Online Sign Identification: Minimization of the Number of Errors in Thresholding Bandits. CoRR abs/2110.09133 (2021) - [i48]Reda Ouhamma, Odalric Maillard, Vianney Perchet:
Stochastic Online Linear Regression: the Forward Algorithm to Replace Ridge. CoRR abs/2111.01602 (2021) - [i47]Evrard Garcelon, Kamalika Chaudhuri, Vianney Perchet, Matteo Pirotta:
Privacy Amplification via Shuffling for Linear Contextual Bandits. CoRR abs/2112.06008 (2021) - 2020
- [c38]Etienne Boursier, Vianney Perchet:
Utility/Privacy Trade-off through the lens of Optimal Transport. AISTATS 2020: 591-601 - [c37]Abbas Mehrabian, Etienne Boursier, Emilie Kaufmann, Vianney Perchet:
A Practical Algorithm for Multiplayer Bandits when Arm Means Vary Among Players. AISTATS 2020: 1211-1221 - [c36]Thomas Nedelec, Clément Calauzènes, Vianney Perchet, Noureddine El Karoui:
Robust Stackelberg buyers in repeated auctions. AISTATS 2020: 1342-1351 - [c35]Xavier Fontaine, Shie Mannor, Vianney Perchet:
An adaptive stochastic optimization algorithm for resource allocation. ALT 2020: 319-363 - [c34]Vianney Perchet:
Finding Robust Nash equilibria. ALT 2020: 725-751 - [c33]Matthieu Jedor, Jonathan Louëdec, Vianney Perchet:
Categorized Bandits. CIRCLE 2020 - [c32]Etienne Boursier, Vianney Perchet:
Selfish Robustness and Equilibria in Multi-Player Bandits. COLT 2020: 530-581 - [c31]Pierre Perrault, Michal Valko, Vianney Perchet:
Covariance-adapting algorithm for semi-bandits with application to sparse outcomes. COLT 2020: 3152-3184 - [c30]Firas Jarboui, Vianney Perchet:
Trajectory representation learning for Multi-Task NMRDP planning. ICPR 2020: 6786-6793 - [c29]Sandrine Péché, Vianney Perchet:
Robustness of Community Detection to Random Geometric Perturbations. NeurIPS 2020 - [c28]Pierre Perrault, Etienne Boursier, Michal Valko, Vianney Perchet:
Statistical Efficiency of Thompson Sampling for Combinatorial Semi-Bandits. NeurIPS 2020 - [i46]Etienne Boursier, Vianney Perchet:
Selfish Robustness and Equilibria in Multi-Player Bandits. CoRR abs/2002.01197 (2020) - [i45]Matthieu Jedor, Jonathan Louëdec, Vianney Perchet:
Categorized Bandits. CoRR abs/2005.01656 (2020) - [i44]Pierre Perrault, Etienne Boursier, Vianney Perchet, Michal Valko:
Statistical Efficiency of Thompson Sampling for Combinatorial Semi-Bandits. CoRR abs/2006.06613 (2020) - [i43]Etienne Boursier, Vianney Perchet, Marco Scarsini:
Speed of Social Learning from Reviews in Non-Stationary Environments. CoRR abs/2007.09996 (2020) - [i42]Evrard Garcelon, Vianney Perchet, Ciara Pike-Burke, Matteo Pirotta:
Local Differentially Private Regret Minimization in Reinforcement Learning. CoRR abs/2010.07778 (2020) - [i41]Sandrine Péché, Vianney Perchet:
Robustness of Community Detection to Random Geometric Perturbations. CoRR abs/2011.04298 (2020) - [i40]Thomas Nedelec, Clément Calauzènes, Noureddine El Karoui, Vianney Perchet:
Learning in repeated auctions. CoRR abs/2011.09365 (2020) - [i39]Matthieu Jedor, Jonathan Louëdec, Vianney Perchet:
Lifelong Learning in Multi-Armed Bandits. CoRR abs/2012.14264 (2020)
2010 – 2019
- 2019
- [c27]Pierre Perrault, Vianney Perchet, Michal Valko:
Finding the bandit in a graph: Sequential search-and-stop. AISTATS 2019: 1668-1677 - [c26]Rémy Degenne, Thomas Nedelec, Clément Calauzènes, Vianney Perchet:
Bridging the gap between regret minimization and best arm identification, with application to A/B tests. AISTATS 2019: 1988-1996 - [c25]Xavier Fontaine, Quentin Berthet, Vianney Perchet:
Regularized Contextual Bandits. AISTATS 2019: 2144-2153 - [c24]Nicolò Cesa-Bianchi, Tommaso Cesari, Vianney Perchet:
Dynamic Pricing with Finitely Many Unknown Valuations. ALT 2019: 247-273 - [c23]Firas Jarboui, Célya Gruson-Daniel, Alain Durmus, Vincent Rocchisani, Sophie-Helene Goulet Ebongue, Anneliese Depoux, Wilfried Kirschenmann, Vianney Perchet:
Markov Decision Process for MOOC Users Behavioral Inference. EMOOCs 2019: 70-80 - [c22]Thomas Nedelec, Noureddine El Karoui, Vianney Perchet:
Learning to bid in revenue-maximizing auctions. ICML 2019: 4781-4789 - [c21]Pierre Perrault, Vianney Perchet, Michal Valko:
Exploiting structure of uncertainty for efficient matroid semi-bandits. ICML 2019: 5123-5132 - [c20]Etienne Boursier, Vianney Perchet:
SIC-MMAB: Synchronisation Involves Communication in Multiplayer Multi-Armed Bandits. NeurIPS 2019: 12048-12057 - [c19]Matthieu Jedor, Vianney Perchet, Jonathan Louëdec:
Categorized Bandits. NeurIPS 2019: 14399-14409 - [c18]Thomas Nedelec, Noureddine El Karoui, Vianney Perchet:
Learning to Bid in Revenue Maximizing Auction. WWW (Companion Volume) 2019: 934-935 - [i38]Pierre Perrault, Vianney Perchet, Michal Valko:
Exploiting Structure of Uncertainty for Efficient Combinatorial Semi-Bandits. CoRR abs/1902.03794 (2019) - [i37]Xavier Fontaine, Shie Mannor, Vianney Perchet:
A Problem-Adaptive Algorithm for Resource Allocation. CoRR abs/1902.04376 (2019) - [i36]Thomas Nedelec, Noureddine El Karoui, Vianney Perchet:
Learning to bid in revenue-maximizing auctions. CoRR abs/1902.10427 (2019) - [i35]Etienne Boursier, Vianney Perchet:
Private Learning and Regularized Optimal Transport. CoRR abs/1905.11148 (2019) - [i34]Nicolò Cesa-Bianchi, Tommaso Cesari, Yishay Mansour, Vianney Perchet:
Repeated A/B Testing. CoRR abs/1905.11797 (2019) - [i33]Clément Calauzènes, Thomas Nedelec, Vianney Perchet, Noureddine El Karoui:
Robust Stackelberg buyers in repeated auctions. CoRR abs/1905.13031 (2019) - [i32]Xavier Fontaine, Pierre Perrault, Vianney Perchet:
Active Linear Regression. CoRR abs/1906.08509 (2019) - [i31]Firas Jarboui, Célya Gruson-Daniel, Alain Durmus, Vincent Rocchisani, Sophie-Helene Goulet Ebongue, Anneliese Depoux, Wilfried Kirschenmann, Vianney Perchet:
Markov Decision Process for MOOC users behavioral inference. CoRR abs/1907.04723 (2019) - [i30]Thomas Nedelec, Jules Baudet, Vianney Perchet, Noureddine El Karoui:
Adversarial learning for revenue-maximizing auctions. CoRR abs/1909.06806 (2019) - 2018
- [j9]János Flesch, Rida Laraki, Vianney Perchet:
Approachability of convex sets in generalized quitting games. Games Econ. Behav. 108: 411-431 (2018) - [c17]Rémy Degenne, Evrard Garcelon, Vianney Perchet:
Bandits with Side Observations: Bounded vs. Logarithmic Regret. UAI 2018: 467-476 - [e1]Sébastien Bubeck, Vianney Perchet, Philippe Rigollet:
Conference On Learning Theory, COLT 2018, Stockholm, Sweden, 6-9 July 2018. Proceedings of Machine Learning Research 75, PMLR 2018 [contents] - [i29]Marc Abeille, Clément Calauzènes, Noureddine El Karoui, Thomas Nedelec, Vianney Perchet:
Explicit shading strategies for repeated truthful auctions. CoRR abs/1805.00256 (2018) - [i28]Pierre Perrault, Vianney Perchet, Michal Valko:
Finding the Bandit in a Graph: Sequential Search-and-Stop. CoRR abs/1806.02282 (2018) - [i27]Nicolò Cesa-Bianchi, Tommaso Cesari, Vianney Perchet:
Dynamic Pricing with Finitely Many Unknown Valuations. CoRR abs/1807.03288 (2018) - [i26]Rémy Degenne, Evrard Garcelon, Vianney Perchet:
Bandits with Side Observations: Bounded vs. Logarithmic Regret. CoRR abs/1807.03558 (2018) - [i25]Thomas Nedelec, Marc Abeille, Clément Calauzènes, Noureddine El Karoui, Benjamin Heymann, Vianney Perchet:
Thresholding the virtual value: a simple method to increase welfare and lower reserve prices in online auction systems. CoRR abs/1808.06979 (2018) - [i24]Etienne Boursier, Vianney Perchet:
SIC-MMAB: Synchronisation Involves Communication in Multiplayer Multi-Armed Bandits. CoRR abs/1809.08151 (2018) - [i23]Rémy Degenne, Thomas Nedelec, Clément Calauzènes, Vianney Perchet:
Bridging the gap between regret minimization and best arm identification, with application to A/B tests. CoRR abs/1810.04088 (2018) - [i22]Xavier Fontaine, Quentin Berthet, Vianney Perchet:
Regularized Contextual Bandits. CoRR abs/1810.05065 (2018) - [i21]Vianney Perchet, Marc Quincampoix:
A differential game on Wasserstein space. Application to weak approachability with partial monitoring. CoRR abs/1811.04575 (2018) - 2017
- [c16]Joon Kwon, Vianney Perchet:
Online Learning and Blackwell Approachability with Partial Monitoring: Optimal Convergence Rates. AISTATS 2017: 604-613 - [c15]Joon Kwon, Vianney Perchet, Claire Vernade:
Sparse Stochastic Bandits. COLT 2017: 1269-1270 - [c14]Quentin Berthet, Vianney Perchet:
Fast Rates for Bandit Optimization with Upper-Confidence Frank-Wolfe. NIPS 2017: 2225-2234 - [c13]Claire Vernade, Olivier Cappé, Vianney Perchet:
Stochastic Bandit Models for Delayed Conversions. UAI 2017 - [i20]Quentin Berthet, Vianney Perchet:
Bandit Optimization with Upper-Confidence Frank-Wolfe. CoRR abs/1702.06917 (2017) - [i19]Thomas Nedelec, Nicolas Le Roux, Vianney Perchet:
A comparative study of counterfactual estimators. CoRR abs/1704.00773 (2017) - [i18]Joon Kwon, Vianney Perchet, Claire Vernade:
Sparse Stochastic Bandits. CoRR abs/1706.01383 (2017) - [i17]Claire Vernade, Olivier Cappé, Vianney Perchet:
Stochastic Bandit Models for Delayed Conversions. CoRR abs/1706.09186 (2017) - 2016
- [j8]Joon Kwon, Vianney Perchet:
Gains and Losses are Fundamentally Different in Regret Minimization: The Sparse Case. J. Mach. Learn. Res. 17: 229:1-229:32 (2016) - [j7]Guillaume Merle, Jean-Marc Roussel, Jean-Jacques Lesage, Vianney Perchet, Nicolas Vayatis:
Quantitative Analysis of Dynamic Fault Trees Based on the Coupling of Structure Functions and Monte Carlo Simulation. Qual. Reliab. Eng. Int. 32(1): 7-18 (2016) - [c12]Francis R. Bach, Vianney Perchet:
Highly-Smooth Zero-th Order Online Optimization. COLT 2016: 257-283 - [c11]János Flesch, Rida Laraki, Vianney Perchet:
Online Learning and Blackwell Approachability in Quitting Games. COLT 2016: 941-942 - [c10]Jonathan Weed, Vianney Perchet, Philippe Rigollet:
Online learning in repeated auctions. COLT 2016: 1562-1583 - [c9]Rémy Degenne, Vianney Perchet:
Anytime optimal algorithms in stochastic multi-armed bandits. ICML 2016: 1587-1595 - [c8]Rémy Degenne, Vianney Perchet:
Combinatorial semi-bandit with known covariance. NIPS 2016: 2964-2972 - [i16]Francis R. Bach, Vianney Perchet:
Highly-Smooth Zero-th Order Online Optimization Vianney Perchet. CoRR abs/1605.08165 (2016) - [i15]János Flesch, Rida Laraki, Vianney Perchet:
Approachability of convex sets in generalized quitting games. CoRR abs/1609.08870 (2016) - [i14]Rémy Degenne, Vianney Perchet:
Combinatorial semi-bandit with known covariance. CoRR abs/1612.01859 (2016) - 2015
- [j6]Vianney Perchet:
Exponential Weight Approachability, Applications to Calibration and Regret Minimization. Dyn. Games Appl. 5(1): 136-153 (2015) - [j5]Vianney Perchet, Marc Quincampoix:
On a Unified Framework for Approachability with Full or Partial Monitoring. Math. Oper. Res. 40(3): 596-610 (2015) - [c7]Vianney Perchet, Philippe Rigollet, Sylvain Chassang, Erik Snowberg:
Batched Bandit Problems. COLT 2015: 1456 - [i13]Jonathan Weed, Vianney Perchet, Philippe Rigollet:
Online learning in repeated auctions. CoRR abs/1511.05720 (2015) - [i12]Joon Kwon, Vianney Perchet:
Gains and Losses are Fundamentally Different in Regret Minimization: The Sparse Case. CoRR abs/1511.08405 (2015) - 2014
- [j4]Shie Mannor, Vianney Perchet, Gilles Stoltz:
Set-valued approachability and online learning with partial monitoring. J. Mach. Learn. Res. 15(1): 3247-3295 (2014) - [j3]Vianney Perchet:
A note on robust Nash equilibria with uncertainties. RAIRO Oper. Res. 48(3): 365-371 (2014) - [c6]Shie Mannor, Vianney Perchet, Gilles Stoltz:
Approachability in unknown games: Online learning meets multi-objective optimization. COLT 2014: 339-355 - [c5]Emile Contal, Vianney Perchet, Nicolas Vayatis:
Gaussian Process Optimization with Mutual Information. ICML 2014: 253-261 - [i11]Shie Mannor, Vianney Perchet, Gilles Stoltz:
Approachability in unknown games: Online learning meets multi-objective optimization. CoRR abs/1402.2043 (2014) - 2013
- [c4]Sébastien Bubeck, Vianney Perchet, Philippe Rigollet:
Bounded regret in stochastic multi-armed bandits. COLT 2013: 122-134 - [c3]Vianney Perchet, Shie Mannor:
Approachability, fast and slow. COLT 2013: 474-488 - [i10]Vianney Perchet:
Nash equilibria with partial monitoring; Computation and Lemke-Howson algorithm. CoRR abs/1301.2662 (2013) - [i9]Vianney Perchet:
Approachability, Regret and Calibration; implications and equivalences. CoRR abs/1301.2663 (2013) - [i8]Vianney Perchet, Marc Quincampoix:
On an unified framework for approachability in games with or without signals. CoRR abs/1301.3609 (2013) - [i7]Sébastien Bubeck, Vianney Perchet, Philippe Rigollet:
Bounded regret in stochastic multi-armed bandits. CoRR abs/1302.1611 (2013) - [i6]Shie Mannor, Vianney Perchet, Gilles Stoltz:
A Primal Condition for Approachability with Partial Monitoring. CoRR abs/1305.5399 (2013) - 2011
- [j2]Vianney Perchet:
Internal Regret with Partial Monitoring: Calibration-Based Optimal Algorithms. J. Mach. Learn. Res. 12: 1893-1921 (2011) - [j1]Vianney Perchet:
Approachability of Convex Sets in Games with Partial Monitoring. J. Optim. Theory Appl. 149(3): 665-677 (2011) - [c2]Shie Mannor, Vianney Perchet, Gilles Stoltz:
Robust approachability and regret minimization in games with partial monitoring. COLT 2011: 515-536 - [i5]