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NeurIPS@Paris 2022 - Schedule of the oral presentations (23/11 afternoon - AMPHI 25)
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TimeThemeTitleSpeakerLink to NeurIPS paper
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13:00-13:15Welcome Speech
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13:15-14:40Reinforcement learning,
online learning,
bandits
(session 1)		Top Two Algorithms Revisited, Marc Jourdan, Rémy Degenne, Dorian Baudry, Rianne de Heide, Emilie KaufmannMarc JourdanLink
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Near Optimal Collaborative Learning in Bandits, Clémence Réda, Sattar Vakili, Emilie KaufmannEmilie KaufmannLink
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Near Instance-Optimal PAC Reinforcement Learning for Deterministic MDPs, Andrea Tirinzoni, Aymen Al-Marjani, Emilie KaufmannEmilie KaufmannLink
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Between Stochastic and Adversarial Online Convex Optimization: Improved Regret Bounds via Smoothness, Sarah Sachs, Hédi Hadiji, Tim van Erven, Cristobal GuzmanSarah SachsLink
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EAGER: Asking and Answering Questions for Automatic Reward Shaping in Language-guided RL, Thomas Carta, Pierre-Yves Oudeyer, Olivier Sigaud, Sylvain LamprierThomas CartaLink
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Meta learning,
federated learning,
distributed learning		MARS: Meta-Learning as Score Matching in the Function Space, Krunoslav Lehman Pavasovic, Jonas Rothfuss, Andreas KrauseKrunoslav Lehman PavasovicLink
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FedPop: A Bayesian Approach for Personalised Federated Learning, Nikita Kotelevskii, Maxime Vono, Eric Moulines, Alain DurmusMaxime VonoLink
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SecureFedYJ: a safe feature Gaussianization protocol for Federated Learning, Tanguy Marchand, Boris Muzellec, Constance Beguier, Jean Ogier du Terrail, Mathieu AndreuxTanguy MarchandLink
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FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Settings, Jean Ogier du Terrail, Samy-Safwan Ayed, Edwige Cyffers et al. Jean du TerrailLink
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On Sample Optimality in Personalized Collaborative and Federated Learning, Mathieu Even, Laurent Massoulié, Kevin ScamanMathieu EvenLink
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Asynchronous SGD beats minibatch SGD under arbitrary delays, Konstantin Mishchenko, Francis Bach, Mathieu Even, Blake Woodworth
Mathieu EvenLink
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Rate-Distortion Theoretic Bounds on Generalization Error for Distributed Learning, Milad Sefidgaran, Romain Chor, Abdellatif Zaidi
Romain ChorLink
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14:40-15:00Coffee Break
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15:00-16:20Applications (session 1)Zero-Shot Video Question Answering via Frozen Bidirectional Language Models, Antoine Yang, Antoine Miech, Josef Sivic, Ivan Laptev, Cordelia SchmidAntoine YangLink
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Diverse Weight Averaging for Out-of-Distribution Generalization, Alexandre Rame, Matthieu Kirchmeyer, Thibaud Rahier, Alain Rakotomamonjy, Patrick Gallinari, Matthieu CordAlexandre RameLink
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The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset, Hugo Laurençon, Lucile Saulnier, Thomas Wang et al.Hugo LaurençonLink
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PrivacyWhen Privacy Meets Partial Information: A Refined Analysis of Differentially Private Bandits, Achraf Azize, Debabrota BasuAchraf AzizeLink
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Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging, Edwige Cyffers, Mathieu Even, Aurélien Bellet, Laurent MassouliéEdwige CyffersLink
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GraphsTemplate based Graph Neural Network with Optimal Transport Distances, Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas CourtyRémi FlamaryLink
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Graph Neural Network Bandits, Parnian Kassraie, Andreas Krause, Ilija BogunovicKassraie ParnianLink
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Collaborative likelihood-ratio estimation over graphs, Alejandro de la Concha, Argyris Kalogeratos, Nicolas VayatisAlejandro de la Concha DuarteLink
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Explanability
Listen to Interpret: Post-hoc Interpretability for Audio Networks with NMF, Jayneel Parekh Sanjeel Parekh, Pavlo Mozharovskyi, Florence d’Alché-Buc, Gaël RichardJayneel ParekhLink
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Harmonizing the object recognition strategies of deep neural networks with humans, Thomas Fel, Ivan Felipe Rodriguez, Drew Linsley, Thomas SerreThomas FelLink
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What I cannot predict I do not understand: a Human-centered Explainability Framework, Julien Colin, Thomas Fel, Remi Cadene, Thomas SerreThomas FelLink
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Making Sense of Dependence: Efficient Black-box Explanations Using Dependence Measure, Paul Novello, Thomas Fel, David Vigouroux
Paul NovelloLink
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Consistent Sufficient Explanations and Minimal Local Rules for explaining the decision of any classifier or regressor, Salim I. Amoukou, Nicolas J.B BrunelSalim AmoukouLink
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Explanation-Guided Learning for Human-AI collaboration, Silvia TulliSilvia TulliLink
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