Debabrota Basu
- Scool (Scool)
- Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL)
- Centre Inria de l'Université de Lille
- Université de Lille
- Centrale Lille
Domaines de recherche
Publications
Publications
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Auditing Fairness under Model Updates: Fundamental Complexity and Property-Preserving UpdatesTwenty-Ninth Annual Conference on Artificial Intelligence and Statistics (AISTATS), May 2026, Tangier, Morocco |
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Unifying (Federated) (Private) High-Dimensional Bandits via ADMMEWRL -- Eighteenth European Workshop on Reinforcement Learning, Sep 2025, Tuebingen, Germany, Germany |
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Optimal Regret of Bandits under Differential PrivacyNeurIPS 2025 - 39th Annual Conference on Neural Information Processing Systems, Dec 2025, San Diego (USA), United States |
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FraPPE: Fast and Efficient Preference-based Pure ExplorationNeurIPS 2025 - 39th Annual Conference on Neural Information Processing Systems, Dec 2025, San Diego (USA), United States |
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When Witnesses Defend: A Witness Graph Topological Layer for Adversarial Graph LearningAAAI Conference on Artificial Intelligence, Feb 2025, Philadelphia, United States |
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Active Fourier Auditor for Estimating Distributional Properties of ML ModelsAAAI Conference on Artificial Intelligence, Feb 2025, Philadelphia, United States |
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FLIPHAT: Joint Differential Privacy for High Dimensional Sparse Linear BanditsAISTATS 2025 – International Conference on Artificial Intelligence and Statistics, May 2025, Phuket, Thailand |
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Stochastic Online Instrumental Variable Regression: Regrets for Endogeneity and Bandit FeedbackAAAI Conference on Artificial Intelligence, Feb 2025, Philadelphia, United States |
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Some Targets Are Harder to Identify than Others: Quantifying the Target-dependent Membership LeakageAISTATS 2025 – International Conference on Artificial Intelligence and Statistics, May 2025, Phuket, Thailand |
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Test-time Verification via Optimal Transport: Coverage, ROC, & Sub-optimalityThe Fourteenth International Conference on Learning Representations (ICLR), Apr 2026, Rio de Janeiro (BRAZIL), Brazil |
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Augmented Bayesian Policy SearchThe Twelfth International Conference on Learning Representations (ICLR), May 2024, Vienna, Austria |
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Pure Exploration in Bandits with Linear ConstraintsInternational Conference on Artificial Intelligence and Statistics, May 2024, Valencia (Espagne), Spain. pp.334-342 |
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Reinforcement Learning in the Wild with Maximum Likelihood-based Model Transfer23rd International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2024, Auckland, New Zealand. pp.516-524, ⟨10.5555/3635637.3662902⟩ |
Concentrated Differential Privacy for Bandits2024 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), IEEE, Apr 2024, Toronto, Canada. pp.78-109, ⟨10.1109/SaTML59370.2024.00013⟩ |
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CRIMED: Lower and Upper Bounds on Regret for Bandits with Unbounded Stochastic CorruptionInternational Conference on Algorithmic Learning Theory (ALT), Feb 2024, San Diego (CA), United States. pp.74-124 |
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Preference-based Pure ExplorationAdvances in Neural Information Processing Systems (NeurIPS), Dec 2024, Vancouver (CA), Canada |
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Learning to Explore with Lagrangians for Bandits under Unknown Linear ConstraintsSeventeenth European Workshop on Reinforcement Learning (EWRL 2024), Oct 2024, Toulouse, France |
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Isoperimetry is All We Need: Langevin Posterior Sampling for RL with Sublinear RegretEWRL -- European Workshop on Reinforcement Learning, Oct 2024, Toulouse, France |
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Open Problem: What is the Complexity of Joint Differential Privacy in Linear Contextual Bandits?Proceedings of Thirty Seventh Conference on Learning Theory, Jul 2024, Edmonton (Alberta), Canada |
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Interactive and Concentrated Differential Privacy for BanditsEWRL 2023 – European Workshop on Reinforcement Learning, Sep 2023, Brussels (Belgium), Belgium |
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From Noisy Fixed-Point Iterations to Private ADMM for Centralized and Federated LearningProceedings of the 40th International Conference on Machine Learning (ICML), Jul 2023, Honolulu, United States |
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Farm-gym: A modular reinforcement learning platform for stochastic agronomic gamesAIAFS 2023 - Artificial Intelligence for Agriculture and Food Systems, Feb 2023, Wahington DC, United States |
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On the Complexity of Differentially Private Best-Arm Identification with Fixed ConfidenceNeurIPS 2023 – Conference on Neural Information Processing Systems, Dec 2023, New Orleans (US), United States. pp.71150--71194 |
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How Biased are Your Features?": Computing Fairness Influence Functions with Global Sensitivity AnalysisFAccT '23: the 2023 ACM Conference on Fairness, Accountability, and Transparency, Jun 2023, Chicago IL, United States. pp.138-148, ⟨10.1145/3593013.3593983⟩ |
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Marich: A Query-efficient Distributionally Equivalent Model Extraction Attack using Public DataAdvances in Neural Information Processing Systems (NeurIPS), Dec 2023, New orleans, USA, United States |
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Bilinear Exponential Family of MDPs: Frequentist Regret Bound with Tractable Exploration & PlanningProceedings of the AAAI Conference on Artificial Intelligence, Feb 2023, Washignton DC, United States. pp.9336-9344, ⟨10.1609/aaai.v37i8.26119⟩ |
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SENTINEL: Taming Uncertainty with Ensemble-based Distributional Reinforcement LearningUAI 2022- Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, Aug 2022, Eindhoven, Netherlands. pp.631-640 |
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When Privacy Meets Partial Information: A Refined Analysis of Differentially Private BanditsAdvances in Neural Information Processing Systems, Dec 2022, New Orleans, United States |
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Algorithmic fairness verification with graphical modelsAAAI-2022 - 36th AAAI Conference on Artificial Intelligence, Feb 2022, Virtual, United States |
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On Meritocracy in Optimal Set SelectionEAAMO 2022- Equity and Access in Algorithms, Mechanisms, and Optimization, ACM, Oct 2022, Arlington, United States |
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Risk-Sensitive Bayesian Games for Multi-Agent Reinforcement Learning under Policy UncertaintyOptLearnMAS@AAMAS, May 2022, Virtual, New Zealand |
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Procrastinated Tree Search: Black-box Optimization with Delayed, Noisy, and Multi-fidelity FeedbackAAAI Conference on Artificial Intelligence, Feb 2022, Virtual, United States. pp.10381-10390 |
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SAAC: Safe Reinforcement Learning as an Adversarial Game of Actor-CriticsRLDM 2022 - The Multi-disciplinary Conference on Reinforcement Learning and Decision Making, Jun 2022, Providence, United States |
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UDO: Universal Database Optimization using Reinforcement LearningProceedings of the VLDB Endowment, Sep 2022, Sydney, Australia. pp.3402-3414, ⟨10.14778/3484224.3484236⟩ |
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Justicia: A Stochastic SAT Approach to Formally Verify FairnessAAAI Conference on Artificial Intelligence, Feb 2021, Virtual, Canada. pp.7554-7563 |
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Demonstrating UDO: A Unified Approach for Optimizing Transaction Code, Physical Design, and System Parameters via Reinforcement LearningSIGMOD/PODS '21: International Conference on Management of Data, Jun 2021, Virtual Event, China. pp.2794-2797, ⟨10.1145/3448016.3452754⟩ |
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Inferential Induction: A Novel Framework for Bayesian Reinforcement Learning"I Can't Believe It's Not Better!" at NeurIPS Workshops, Dec 2020, Vancouver, Canada. pp.43-52 |
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Confidentialité différentielle à risque : Relier les sources d’aléa et un budget de confidentialitéBDA 2020 - 36ème Conférence sur la Gestion de Données – Principes, Technologies et Applications, Oct 2020, Paris / Virtuel, France |
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Construction and Random Generation of Hypergraphs with Prescribed Degree and Dimension SequencesDEXA, 2020, Bratislava, Slovenia |
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BelMan: An Information-Geometric Approach to Stochastic BanditsECML/PKDD - The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Sep 2019, Würzburg, Germany |
How to Find the Best Rated Items on a Likert Scale and How Many Ratings Are EnoughDatabase and Expert Systems Applications - 28th International Conference, DEXA 2017, Lyon, France, August 28-31, 2017, Proceedings, Part II, 2017, Lyon, France. pp.351-359, ⟨10.1007/978-3-319-64471-4_28⟩ |
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Top-k Queries Over Uncertain ScoresOn the Move to Meaningful Internet Systems (OTM-CoopIS 2016), Oct 2016, Rhodes, Greece. pp.245-262, ⟨10.1007/978-3-319-48472-3_14⟩ |
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Cost-Model Oblivious Database Tuning with Reinforcement LearningDEXA, Sep 2015, Valencia, Spain. pp.253-268 |
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Apprentissage par renforcement pour optimiser les bases de donnéees indépendamment du modèle de coûtBDA, Sep 2015, Porquerolles, France |
Federated Learning of Oligonucleotide Drug Molecule Thermodynamics with Differentially Private ADMM-Based SVMMachine Learning and Principles and Practice of Knowledge Discovery in Databases, 1525, Springer International Publishing; Springer International Publishing, pp.459-467, 2021, Communications in Computer and Information Science, ⟨10.1007/978-3-030-93733-1_34⟩ |
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Regularized Cost-Model Oblivious Database Tuning with Reinforcement LearningAbdelkader Hameurlain; Josef Küng; Roland Wagner; Qimin Chen. Transactions on Large-Scale Data- and Knowledge-Centered Systems XXVIII, 9940, Springer Verlag, pp.96-132, 2016, Lecture Notes in Computer Science, ⟨10.1007/978-3-662-53455-7_5⟩ |