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Publications


88 documents

Articles dans une revue12 document

  • Bastien Doignies, David Coeurjolly, Nicolas Bonneel, Julie Digne, Jean-Claude Iehl, et al.. Differentiable Owen Scrambling. ACM Transactions on Graphics, 2024, proceeding of Siggraph ASIA 2024, 43 (6), pp.255. ⟨10.1145/3687764⟩. ⟨hal-04721127⟩
  • Eloi Tanguy, Rémi Flamary, Julie Delon. Reconstructing discrete measures from projections. Consequences on the empirical Sliced Wasserstein Distance. Comptes Rendus. Mathématique, 2024, 362, pp.1121--1129. ⟨hal-04232769v2⟩
  • Akwum Onwunta, Clément Royer. Complexity Analysis of Regularization Methods for Implicitly Constrained Least Squares. Journal of Scientific Computing, 2024, 101 (3), pp.54. ⟨10.1007/s10915-024-02691-2⟩. ⟨hal-04745284⟩
  • Prachi Kashikar, Olivier Sentieys, Sharad Sinha. Combining Weight Approximation, Sharing and Retraining for Neural Network Model Compression. ACM Transactions on Embedded Computing Systems (TECS), 2024, 23, pp.1 - 23. ⟨10.1145/3687466⟩. ⟨hal-04764621⟩
  • Panayotis Mertikopoulos, William H Sandholm. Nested replicator dynamics, nested logit choice, and similarity-based learning. Journal of Economic Theory, 2024, 220, pp.105881. ⟨10.1016/j.jet.2024.105881⟩. ⟨hal-04733800⟩
  • Panayotis Mertikopoulos, Heinrich H Nax, Bary S R Pradelski. Quick or cheap? Breaking points in dynamic markets. Journal of Mathematical Economics, 2024, 112, pp.102987. ⟨10.1016/j.jmateco.2024.102987⟩. ⟨hal-04664218⟩
  • Antoine Picard-Weibel, Gabriel Capson-Tojo, Benjamin Guedj, Roman Moscoviz. Bayesian Uncertainty Quantification for Anaerobic Digestion models. Bioresource Technology, 2024, 394, ⟨10.1016/j.biortech.2023.130147⟩. ⟨hal-04592670⟩
  • Marco Campion, Mila Dalla Preda, Roberto Giacobazzi, Caterina Urban. Monotonicity and the Precision of Program Analysis. Proceedings of the ACM on Programming Languages, 2024, 8 (POPL), pp.1629-1662. ⟨10.1145/3632897⟩. ⟨hal-04423578⟩
  • Waïss Azizian, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos. The rate of convergence of Bregman proximal methods: Local geometry vs. regularity vs. sharpness. SIAM Journal on Optimization, 2024, 34 (3), pp.2440-2471. ⟨10.1137/23M1580218⟩. ⟨hal-04307796⟩
  • Timothée Mathieu, Debabrota Basu, Odalric-Ambrym Maillard. Bandits Corrupted by Nature: Lower Bounds on Regret and Robust Optimistic Algorithms. Transactions on Machine Learning Research Journal, 2024. ⟨hal-04615733⟩
  • Antonin Chambolle, Michał Łasica. Inclusion and estimates for the jumps of minimizers in variational denoising. SIAM Journal on Imaging Sciences, 2023, 17 (3), pp.1844-1878. ⟨10.1137/23M1627948⟩. ⟨hal-04323807v2⟩
  • Eloi Tanguy, Rémi Flamary, Julie Delon. Properties of Discrete Sliced Wasserstein Losses. Mathematics of Computation, 2023, ⟨https://doi.org/10.1090/mcom/3994⟩. ⟨hal-04232766v3⟩

Communications dans un congrès40 document

  • Yannis Karmim, Marc Lafon, Raphaël Fournier-S'Niehotta, Nicolas Thome. Supra-Laplacian Encoding for Transformer on Dynamic Graphs. The Thirty-eighth Annual Conference on Neural Information Processing Systems, Dec 2024, Vancouver (CA), Canada. ⟨hal-04785441⟩
  • Adrienne Tuynman, Rémy Degenne, Emilie Kaufmann. Finding good policies in average-reward Markov Decision Processes without prior knowledge. NeurIPS, Dec 2024, Vancouver (Canada), Canada. ⟨hal-04809429⟩
  • Riccardo Poiani, Rémy Degenne, Emilie Kaufmann, Alberto Maria Metelli, Marcello Restelli. Optimal Multi-Fidelity Best-Arm Identification. Advances in Neural Information Processing Systems (NeurIPS), Dec 2024, Vancouver (BC), Canada. ⟨hal-04811199⟩
  • Clément Bonet, Théo Uscidda, Adam David, Pierre-Cyril Aubin-Frankowski, Anna Korba. Mirror and Preconditioned Gradient Descent in Wasserstein Space. Neural Information Processing Systems (NeurIPS), Dec 2024, Vancouver, Canada. ⟨hal-04703424⟩
  • Antoine Picard-Weibel, Roman Moscoviz, Benjamin Guedj. Learning via Surrogate PAC-Bayes. NeurIPS 2024, Dec 2024, Vancouver, Canada. ⟨hal-04731841v2⟩
  • Reuben Adams, John Shawe-Taylor, Benjamin Guedj. Controlling Multiple Errors Simultaneously with a PAC-Bayes Bound. NeurIPS 2024, Dec 2024, Vancouver, Canada. ⟨hal-03573458⟩
  • Ayoub Ajarra, Bishwamittra Ghosh, Debabrota Basu. Active Fourier Auditor for Estimating Distributional Properties of ML Models. NeurIPS 2024 Workshop on Regulatable ML, Dec 2024, Vancouver (BC), Canada. ⟨hal-04733059⟩
  • Apurv Shukla, Debabrota Basu. Preference-based Pure Exploration. Advances in Neural Information Processing Systems (NeurIPS), Dec 2024, Vancouver (CA), Canada. ⟨hal-04733134⟩
  • Erwan Fagnou, Paul Caillon, Blaise Delattre, Alexandre Allauzen. Chain and Causal Attention for Efficient Entity Tracking. Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), Association for Computational Linguistics, Nov 2024, Miami, United States. ⟨hal-04731420⟩
  • Zhuofan Xu, Benedikt Bollig, Matthias Függer, Thomas Nowak. Permutation Equivariant Deep Reinforcement Learning for Multi-Armed Bandit. 36th IEEE International Conference on Tools with Artificial Intelligence (ICTAI), Oct 2024, Herndon, United States. ⟨hal-04787072⟩
  • Denis Mazzucato, Marco Campion, Caterina Urban. Quantitative Static Timing Analysis. 31st Static Analysis Symposium (SAS 2024), Roberto Giacobazzi; Alessandra Gorla; Marco Campion, Oct 2024, Pasadena, CA, United States. ⟨hal-04669723⟩
  • Ben Batten, Yang Zheng, Alessandro De Palma, Panagiotis Kouvaros, Alessio Lomuscio. Verification of Geometric Robustness of Neural Networks via Piecewise Linear Approximation and Lipschitz Optimisation. ECAI 2024 - European Conference on Artificial Intelligence, Oct 2024, Santiago de Compostela, Spain. ⟨hal-04727955⟩
  • Udvas Das, Debabrota Basu. Learning to Explore with Lagrangians for Bandits under Unknown Linear Constraints. Seventeenth European Workshop on Reinforcement Learning (EWRL), Oct 2024, Toulouse, France. ⟨hal-04784911⟩
  • Nicolo Bellarmino, Alberto Bosio, Riccardo Cantoro, Annachiara Ruospo, Ernesto Sanchez, et al.. Investigating on Gradient Regularization for Testing Neural Networks. LOD 2024 : 10th International Conference on machine Learning, Optimization and Data science, Sep 2024, Riva de Sole, Italy. ⟨hal-04604264⟩
  • Audrey Poinsot, Alessandro Leite, Nicolas Chesneau, Michele Sebag, Marc Schoenauer. Learning Structural Causal Models through Deep Generative Models: Methods, Guarantees, and Challenges. IJCAI 2024 - Thirty-Third International Joint Conference on Artificial Intelligence, Aug 2024, Jeju, South Korea. pp.8207-8215, ⟨10.24963/ijcai.2024/907⟩. ⟨hal-04706985⟩
  • Thomas Firmin, Pierre Boulet, El-Ghazali Talbi. Asynchronous Multi-fidelity Hyperparameter Optimization Of Spiking Neural Networks. International Conference on Neuromorphic Systems (ICONS 2024), Jul 2024, Washington, United States. ⟨hal-04781629⟩
  • Batiste Le Bars, Aurélien Bellet, Marc Tommasi, Kevin Scaman, Giovanni Neglia. Improved Stability and Generalization Guarantees of the Decentralized SGD Algorithm. ICML 2024 - The Forty-first International Conference on Machine Learning, Jul 2024, Vienne, Austria. ⟨hal-04611418⟩
  • Waïss Azizian, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos. What is the long-run distribution of stochastic gradient descent? A large deviations analysis. ICML 2024 - 41st International Conference on Machine Learning, Jul 2024, Vienna, Austria. pp.1-70. ⟨hal-04629305⟩
  • Sibylle Marcotte, Rémi Gribonval, Gabriel Peyré. Keep the Momentum: Conservation Laws beyond Euclidean Gradient Flows. 41st International Conference on Machine Learning, Jul 2024, Vienna, Austria. ⟨hal-04590932⟩
  • Romain Xu-Darme, Aymeric Varasse, Alban Grastien, Julien Girard, Zakaria Chihani. CaBRNet, an open-source library for developing and evaluating Case-Based Reasoning Models. xAI 2024 - The 2nd World Conference on eXplainable Artificial Intelligence, Jul 2024, La valette, Malta. pp.TBD. ⟨cea-04688217v2⟩
  • Davide Legacci, Panayotis Mertikopoulos, Bary Pradelski. A geometric decomposition of finite games: Convergence vs. recurrence under exponential weights. ICML 2024 - 41st International Conference on Machine Learning, Jul 2024, Vienna, Austria. ⟨hal-04629310⟩
  • Andreas Kontogiannis, Vasilis Pollatos, Sotiris Kanellopoulos, Panayotis Mertikopoulos, Aris Pagourtzis, et al.. The computational complexity of finding second-order stationary points. ICML 2024 - 41st International Conference on Machine Learning, Jul 2024, Vienna, Austria. ⟨hal-04629307⟩
  • Achraf Azize, Debabrota Basu. 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. ⟨hal-04621903⟩
  • Denis Mazzucato, Marco Campion, Caterina Urban. Quantitative Input Usage Static Analysis. NASA Formal Methods 2024, Jun 2024, Moffett Field (CA), United States. pp.79-98, ⟨10.1007/978-3-031-60698-4_5⟩. ⟨hal-04339001v3⟩
  • Marcello Traiola, Salvatore Pappalardo, Ali Piri, Annachiara Ruospo, Bastien Deveautour, et al.. Approximate Fault-Tolerant Neural Network Systems. ETS 2024 - 29th IEEE European Test Symposium, May 2024, La Haye, Netherlands. pp.1-10, ⟨10.1109/ETS61313.2024.10567290⟩. ⟨hal-04674818⟩
  • Lise Le Boudec, Emmanuel de Bézenac, Louis Serrano, Yuan Yin, Patrick Gallinari. Learning iterative algorithms to solve PDEs. ICLR 2024 Workshop on AI4DifferentialEquations In Science, ICLR 2024 Workshop, May 2024, Vienne (Austria), France. https://ai4diffeqtnsinsci.github.io. ⟨hal-04821571⟩
  • Alessandro De Palma, Rudy Bunel, Krishnamurthy Dvijotham, M Pawan Kumar, Robert Stanforth, et al.. Expressive Losses for Verified Robustness via Convex Combinations. ICLR 2024 - International Conference on Learning Representations, May 2024, Vienna, Austria. ⟨hal-04511820⟩
  • Marien Renaud, Jiaming Liu, Valentin de Bortoli, Andrés Almansa, Ulugbek Kamilov. Plug-and-Play Posterior Sampling under Mismatched Measurement and Prior Models. (ICLR 2024) The Twelfth International Conference on Learning Representations, May 2024, Wien, Austria. ⟨hal-04307874⟩
  • Mehdi Zadem, Sergio Mover, Sergio Mover, Sao Mai Nguyen. Reconciling Spatial and Temporal Abstractions for Goal Representation. ICLR 2024 - The Twelfth International Conference on Learning Representations, May 2024, Vienna, Austria. ⟨hal-04629549⟩
  • Hannes Eriksson, Tommy Tram, Debabrota Basu, Mina Alibeigi, Christos Dimitrakakis. Reinforcement Learning in the Wild with Maximum Likelihood-based Model Transfer. 23rd International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2024, Auckland, New Zealand. pp.516-524, ⟨10.5555/3635637.3662902⟩. ⟨hal-04260795⟩
  • Achraf Azize, Debabrota Basu. Concentrated Differential Privacy for Bandits. 2024 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), IEEE, Apr 2024, Toronto, Canada. pp.78-109, ⟨10.1109/SaTML59370.2024.00013⟩. ⟨hal-04611650⟩
  • Cristiana Bolchini, Alberto Bosio. Resilience of deep learning applications: where we are and where we want to go. 2024 Design, Automation & Test in Europe Conference & Exhibition (DATE), Mar 2024, Valencia (Espagne), Spain. ⟨hal-04674837⟩
  • Sami Ben Ali, Silviu-Ioan Filip, Olivier Sentieys. A Stochastic Rounding-Enabled Low-Precision Floating-Point MAC for DNN Training. DATE 2024 - 27th IEEE/ACM Design, Automation and Test in Europe, Mar 2024, Valencia, Spain. pp.1-6. ⟨hal-04380270v3⟩
  • Florian Le Bronnec, Song Duong, Mathieu Ravaut, Alexandre Allauzen, Nancy F. Chen, et al.. LOCOST: State-Space Models for Long Document Abstractive Summarization. European Chapter of the Association for Computational Linguistics (EACL), Mar 2024, St. Julian’s, Malta. ⟨hal-04438465⟩
  • Shubhada Agrawal, Timothée Mathieu, Debabrota Basu, Odalric-Ambrym Maillard. CRIMED: Lower and Upper Bounds on Regret for Bandits with Unbounded Stochastic Corruption. International Conference on Algorithmic Learning Theory (ALT), Feb 2024, San Diego (CA), United States. pp.74-124. ⟨hal-04260464⟩
  • Abhinandan Pal, Francesco Ranzato, Caterina Urban, Marco Zanella. Abstract Interpretation-Based Feature Importance for Support Vector Machines. 25th International Conference on Verification, Model Checking, and Abstract Interpretation (VMCAI 2024), Jan 2024, London, United Kingdom. pp.27-49, ⟨10.1007/978-3-031-50524-9_2⟩. ⟨hal-04378817⟩
  • Cédric Gernigon, Silviu-Ioan Filip, Olivier Sentieys, Clément Coggiola, Mickael Bruno. AdaQAT: Adaptive Bit-Width Quantization-Aware Training. IEEE 6th International Conference on AI Circuits and Systems (AICAS), 2024, Abu Dhabi, United Arab Emirates. ⟨hal-04549245⟩
  • Antonin Joly, Nicolas Keriven. Graph Coarsening with Message-Passing Guarantees. Advances in Neural Information Processing Systems (NeurIPS), 2024, Vancouver, Canada. ⟨hal-04617519⟩
  • Léo Henry, Blaise Genest, Alexandre Drewery. Reinforcement Planning for effective ε-optimal policies in dense time with discontinuities. 43rd IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science, Dec 2023, hyderabad, India. ⟨10.4230/LIPIcs⟩. ⟨hal-04280462⟩
  • Achraf Azize, Marc Jourdan, Aymen Al Marjani, Debabrota Basu. On the Complexity of Differentially Private Best-Arm Identification with Fixed Confidence. NeurIPS 2023 – Conference on Neural Information Processing Systems, Dec 2023, New Orleans (US), United States. pp.71150--71194. ⟨hal-04215474⟩

Ouvrages (y compris édition critique et traduction)1 document


Pré-publications, Documents de travail34 document

  • Antoine Guennec, Jean-François Aujol, Yann Traonmilin. Joint structure-texture low dimensional modeling for image decomposition with a plug and play framework. 2024. ⟨hal-04648963v3⟩
  • Pablo de Oliveira Castro, El-Mehdi El Arar, Eric Petit, Devan Sohier. Error Analysis of Sum-Product Algorithms under Stochastic Rounding. 2024. ⟨hal-04787542v2⟩
  • Tom Hubrecht, Orégane Desrentes, Florent de Dinechin. Activations in Low Precision with High Accuracy. 2024. ⟨hal-04776745⟩
  • Antoine Gonon, Léon Zheng, Pascal Carrivain, Quoc-Tung Le. Fast inference with Kronecker-sparse matrices. 2024. ⟨hal-04584450v4⟩
  • Chao Han, Debabrota Basu, Michael Mangan, Eleni Vasilaki, Aditya Gilra. Dynamical-VAE-based Hindsight to Learn the Causal Dynamics of Factored-POMDPs. 2024. ⟨hal-04785076⟩
  • Joubine Aghili, Romain Hild, Victor Michel-Dansac, Vincent Vigon, Emmanuel Franck. Accelerating the convergence of Newton's method for nonlinear elliptic PDEs using Fourier neural operators. 2024. ⟨hal-04440076v3⟩
  • Charles Dossal, Samuel Hurault, Nicolas Papadakis. Optimization with First Order Algorithms. 2024. ⟨hal-04755998⟩
  • Debabrota Basu, Sourav Chakraborty, Debarshi Chanda, Buddha Dev Das, Arijit Ghosh, et al.. Testing Credibility of Public and Private Surveys through the Lens of Regression. 2024. ⟨hal-04733076⟩
  • Julien Hermant, Marien Renaud, Jean-François Aujol, Charles Dossal, Aude Rondepierre. Gradient correlation is needed to accelerate SGD with momentum. 2024. ⟨hal-04728121⟩
  • Yann Traonmilin, Jean François Aujol, Antoine Guennec. Towards optimal algorithms for the recovery of low-dimensional models with linear rates. 2024. ⟨hal-04725337⟩
  • Naheed Anjum Arafat, Debabrota Basu, Yulia Gel, Yuzhou Chen. When Witnesses Defend: A Witness Graph Topological Layer for Adversarial Graph Learning. 2024. ⟨hal-04708183⟩
  • Aurélien Garivier, Emmanuel Pilliat. On Sparsity and Sub-Gaussianity in the Johnson-Lindenstrauss Lemma. 2024. ⟨hal-04690731v2⟩
  • Reabetswe M. Nkhumise, Debabrota Basu, Tony J. Prescott, Aditya Gilra. Measuring Exploration in Reinforcement Learning via Optimal Transport in Policy Space. 2024. ⟨hal-04702986⟩
  • El-Mehdi El Arar, Massimiliano Fasi, Silviu-Ioan Filip, Mantas Mikaitis. Probabilistic error analysis of limited-precision stochastic rounding. 2024. ⟨hal-04665809v2⟩
  • Amaury Bélières--Frendo, Emmanuel Franck, Victor Michel-Dansac, Yannick Privat. Volume-Preserving Geometric Shape Optimization of the Dirichlet Energy Using Variational Neural Networks. 2024. ⟨hal-04663197v2⟩
  • Erell Gachon, Jérémie Bigot, Elsa Cazelles, Aguirre Mimoun, Jean-Philippe Vial. Low dimensional representation of multi-patient flow cytometry datasets using optimal transport for minimal residual disease detection in leukemia. 2024. ⟨hal-04661639⟩
  • Eloi Tanguy, Agnès Desolneux, Julie Delon. Constrained Approximate Optimal Transport Maps. 2024. ⟨hal-04705433⟩
  • Sunrit Chakraborty, Saptarshi Roy, Debabrota Basu. FLIPHAT: Joint Differential Privacy for High Dimensional Sparse Linear Bandits. 2024. ⟨hal-04615697⟩
  • Achraf Azize, Marc Jourdan, Aymen Al Marjani, Debabrota Basu. Differentially Private Best-Arm Identification. 2024. ⟨hal-04615690⟩
  • Léo Portales, Elsa Cazelles, Edouard Pauwels. On the sequential convergence of Lloyd's algorithms. 2024. ⟨hal-04593982v2⟩
  • Julien Hermant, Jean-François Aujol, Charles Dossal, Aude Rondepierre. Study of the behaviour of Nesterov Accelerated Gradient in a non convex setting: the strongly quasar convex case. 2024. ⟨hal-04589853⟩
  • Antoine Gonon, Nicolas Brisebarre, Elisa Riccietti, Rémi Gribonval. Path-metrics, pruning, and generalization. 2024. ⟨hal-04584311v2⟩
  • Eric Goubault, Sylvie Putot. A Zonotopic Dempster-Shafer Approach to the Quantitative Verification of Neural Networks. 2024. ⟨hal-04546350v2⟩
  • Antonin Chambolle, Daniele de Gennaro, Massimiliano Morini. Discrete-to-continuous crystalline curvature flows. 2024. ⟨hal-04500307v2⟩
  • Eloi Tanguy. Convergence of SGD for Training Neural Networks with Sliced Wasserstein Losses. 2024. ⟨hal-04232792v2⟩
  • Jean-François Aujol, Charles Dossal, Hippolyte Labarrière, Aude Rondepierre. Heavy Ball Momentum for Non-Strongly Convex Optimization. 2024. ⟨hal-04500652⟩
  • Paul Viallard, Maxime Haddouche, Umut Şimşekli, Benjamin Guedj. Tighter Generalisation Bounds via Interpolation. 2024. ⟨hal-04456925⟩
  • Maxime Haddouche, Paul Viallard, Umut Şimşekli, Benjamin Guedj. A PAC-Bayesian Link Between Generalisation and Flat Minima. 2024. ⟨hal-04455639⟩
  • Vitalii Emelianov, Michaël Perrot. On the Impact of Output Perturbation on Fairness in Binary Linear Classification. 2024. ⟨hal-04440982⟩
  • Rémi Leluc, Aymeric Dieuleveut, François Portier, Johan Segers, Aigerim Zhuman. Sliced-Wasserstein Estimation with Spherical Harmonics as Control Variates. 2024. ⟨hal-04438124⟩
  • Fryderyk Falniowski, Panayotis Mertikopoulos. On the discrete-time origins of the replicator dynamics: From convergence to instability and chaos. 2024. ⟨hal-04629311⟩
  • Iosif Lytras, Panayotis Mertikopoulos. Tamed Langevin sampling under weaker conditions. 2024. ⟨hal-04629313⟩
  • Quoc-Tung Le, Rémi Gribonval, Elisa Riccietti, Léon Zheng. Butterfly factorization with error guarantees. 2024. ⟨hal-04763712⟩
  • Quentin Mérigot, Luca Nenna, Hamza Ennaji, Brendan Pass. Robust risk management via multi-marginal optimal transport. 2022. ⟨hal-03852245⟩

Rapports1 document

  • Maxime Amisse, Mélissa Faur, Lucie Gonard, André Orcesi. Promouvoir des modèles d’intelligence artificielle frugale pour et par les politiques publiques. Ecole des Ponts Paris Tech, Paris-France. 2024. ⟨hal-04510171⟩

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