38 Hi! PARIS Papers Accepted for the 38th Annual NeurIPS Conference
From December 10 to 15, Hi! PARIS researchers participated in the 38th annual Conference on Neural Information Processing Systems (NeurIPS 2024) in Vancouver, Canada.
This year, a total of 38 research papers by Hi! PARIS afilliates were accepted after the demanding and thorough peer-review process for their significant methodological contribution to the field. This achievement recognizes the successful work of researchers from Hi! PARIS and renowned partner institutions.
This milestone highlights the center’s leadership in AI research. The accepted papers cover diverse topics such as machine learning, natural language processing, reinforcement learning, and more. In addition to the main conference, Hi! PARIS researchers also contributed to thematic workshops, fostering collaboration and innovation.
This achievement underscores Hi! PARIS’s commitment to advancing AI for societal impact and strengthening its position as a key player in the global AI ecosystem.
Congratulations to our researchers!
Here is a list of papers accepted at NeurIPS 2024 that include at least one author affiliated with Hi! PARIS:
| Title | Authors |
|---|---|
| Divide-and-Conquer Posterior Sampling for Denoising Diffusion Priors | Yazid Janati, Badr MOUFAD, Alain Durmus, Eric Moulines, Jimmy Olsson |
| Gaussian Approximation and Multiplier Bootstrap for Polyak-Ruppert Averaged Linear Stochastic Approximation with Applications to TD Learning | Sergey Samsonov, Eric Moulines, Qi-Man Shao, Zhuo-Song Zhang, Alexey Naumov |
| Learning to Mitigate Externalities: the Coase Theorem with Hindsight Rationality | Antoine Scheid, Aymeric Capitaine, Etienne Boursier, Eric Moulines, Michael Jordan, Alain Durmus |
| Activation Map Compression through Tensor Decomposition for Deep Learning | Le-Trung Nguyen, Aël Quélennec, Enzo Tartaglione, Samuel Tardieu, Van-Tam Nguyen |
| Annealed Multiple Choice Learning: Overcoming Limitations of Winner-Takes-All with Annealing | David Perera, Victor Letzelter, Theo Mariotte, Adrien Cortes, Gaël Richard, Slim Essid, Mickael Chen |
| General Detection-Based Text Line Recognition | Raphael Baena, Syrine Kalleli, Mathieu Aubry |
| Asymptotics of Alpha-Divergence Variational Inference Algorithms with Exponential Families | François Bertholom, Randal Douc, François Roueff |
| Logarithmic Smoothing for Pessimistic Off-Policy Evaluation, Selection and Learning | Otmane Sakhi, Imad Aouali, Pierre Alquier, Nicolas Chopin |
| GENOT: Entropic (Gromov) Wasserstein Flow Matching with Applications to Single-Cell Genomics | Dominik Klein, Théo Uscidda, Fabian Theis, Marco Cuturi |
| Learning Elastic Costs to Shape Monge Displacements | Michal Klein, Aram-Alexandre Pooladian, Pierre Ablin, Eugene Ndiaye, Jonathan Niles-Weed, Marco Cuturi |
| Progressive Entropic Optimal Transport Solvers | Parnian Kassraie, Aram-Alexandre Pooladian, Michal Klein, James Thornton, Jonathan Niles-Weed, Marco Cuturi |
| Any2Graph: Deep End-To-End Supervised Graph Prediction With An Optimal Transport Loss | Paul KRZAKALA, Junjie Yang, Rémi Flamary, Florence d'Alché-Buc, Charlotte Laclau, Matthieu Labeau |
| Theoretical Guarantees in KL for Diffusion Flow Matching | Marta Gentiloni Silveri, Alain Durmus, Giovanni Conforti |
| Piecewise Deterministic Generative Models | Andrea Bertazzi, Alain Durmus, Dario Shariatian, Umut Simsekli, Eric Moulines |
| Unravelling in Collaborative Learning | Aymeric Capitaine, Etienne Boursier, Antoine Scheid, Eric Moulines, Michael Jordan, El-Mahdi El-Mhamdi, Alain Durmus |
| Shape Analysis for Time Series | Thibaut Germain, Samuel Gruffaz, Charles Truong, Alain Durmus, Laurent Oudre |
| Watermarking Makes Language Models Radioactive | Tom Sander, Pierre Fernandez, Alain Durmus, Matthijs Douze, Teddy Furon |
| Continuous Product Graph Neural Networks | Aref Einizade, Fragkiskos Malliaros, Jhony Heriberto Giraldo Zuluaga |
| An Eye for an Ear: Zero-Shot Audio Description Leveraging an Image Captioner with Audio-Visual Token Distribution Matching | Hugo Malard, Michel Olvera, Stéphane Lathulière, Slim Essid |
| Frustratingly Easy Test-Time Adaptation of Vision-Language Models | Matteo Farina, Gianni Franchi, Giovanni Iacca, Massimiliano Mancini, Elisa Ricci |
| Lyapunov Functions: A Long-Standing Open Problem in Mathematics, with Symbolic Transformers | Alberto Alfarano, Francois Charton, Amaury Hayat |
| DU-Shapley: A Shapley Value Proxy for Efficient Dataset Valuation | Maxime Vono, Benjamin Heymann, Felipe Garrido Lucero, Vianney Perchet, Patrick Loiseau |
| Constrained Sampling with Primal-Dual Langevin Monte Carlo | Luiz F. O. Chamon, Mohammad Reza Karimi Jaghargh, Anna Korba |
| Mirror and Preconditioned Gradient Descent in Wasserstein Space | Clément Bonet, Théo Uscidda, Adam David, Pierre-Cyril Aubin-Frankowski, Anna Korba |
| Statistical and Geometrical Properties of the Kernel Kullback-Leibler Divergence | Anna Korba, Francis Bach, Clémentine CHAZAL |
| Near-Optimal Distributionally Robust Reinforcement Learning with General Lp Norms | Pierre Clavier, Laixi Shi, Erwan Le Pennec, Eric Mazumdar, Adam Wierman, Matthieu Geist |
| Neural Conditional Probability for Uncertainty Quantification | Vladimir Kostic, Grégoire Pacreau, Giacomo Turri, Pietro Novelli, Karim Lounici, Massimiliano Pontil |
| If You Want to Be Robust, Be Wary of Initialization | Sofiane ENNADIR, Johannes Lutzeyer, Michalis Vazirgiannis, El Houcine Bergou |
| ManiPose: Manifold-Constrained Multi-Hypothesis 3D Human Pose Estimation | Cédric ROMMEL, Victor Letzelter, Nermin Samet, Renaud Marlet, Matthieu Cord, Patrick Pérez, Eduardo Valle |
| DeBaRA: Denoising-Based 3D Room Arrangement Generation | Léopold Maillard, Nicolas Sereyjol-Garros, Tom Durand, Maks Ovsjanikov |
| The Value of Reward Lookahead in Reinforcement Learning | Nadav Merlis, Dorian Baudry, Vianney Perchet |
| Addressing Bias in Online Selection with Limited Budget of Comparisons | Ziyad Benomar, Evgenii Chzhen, Nicolas Schreuder, Vianney Perchet |
| Strategic Multi-Armed Bandit Problems Under Debt-Free Reporting | Ahmed Ben Yahmed, Clément Calauzènes, Vianney Perchet |
| Improved Algorithms for Contextual Dynamic Pricing | Matilde Tullii, Solenne Gaucher, Nadav Merlis, Vianney Perchet |
| Improved Learning Rates in Multi-Unit Uniform Price Auctions | Marius Potfer, Dorian Baudry, Hugo Richard, Vianney Perchet, Cheng Wan |
| Local and Adaptive Mirror Descents in Extensive-Form Games | Côme Fiegel, Pierre Ménard, Tadashi Kozuno, Remi Munos, Vianney Perchet, Michal Valko |
| Optimizing the Coalition Gain in Online Auctions with Greedy Structured Bandits | Dorian Baudry, Hugo Richard, Maria Cherifa, Vianney Perchet, Clément Calauzènes |
| Lookback Prophet Inequalities | Ziyad Benomar, Dorian Baudry, Vianney Perchet |