A few papers co-authored by Criteos recently accepted at many premiere ML venues! Congrats to all and their co-authors.
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EC 2022
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Vianney Perchet, Philippe Rigollet, Thibaut Le Gouic, ”An algorithmic solution to the Blotto game using multi-marginal couplings”,
An algorithmic solution to the Blotto game using multi-marginal couplings
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ICML 2022
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Matthieu Kirchmeyer (Criteo and Sorbonne Université) and Yuan Yin (Sorbonne Université); Jérémie Donà (Sorbonne Université); Nicolas Baskiotis (Sorbonne Université); Alain Rakotomamonjy (Criteo and Université de Rouen); @Patrick Gallinari (Criteo and Sorbonne Université), “Generalizing to New Physical Systems via Context-Informed Dynamics Model” https://arxiv.org/abs/2202.01889
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Jean-Yves Franceschi (Criteo, work partially done at Sorbonne Université), Emmanuel de Bézenac (ETH Zürich, work partially done at Sorbonne Université), Ibrahim Ayed (Sorbonne Université, Thales), Mickaël Chen (Valeo.ai), Sylvain Lamprier (Sorbonne Université) and Patrick Gallinari (Criteo, Sorbonne Université), “A Neural Tangent Kernel Perspective of GANs”
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Matthieu Martin, Panagiotis Mertikopoulos, Thibaud Rahier and Houssam Zenati, “Nested Exponential Weights and the Red Bus / Blue Bus Paradox“
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Kimon Antonakopoulos, Dong Quan Vu, Volkan Cevher, Kfir Levy, and Panagiotis Mertikopoulos, “Scaling up Universal Methods for Convex Optimization“
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Kimon Antonakopoulos, @Panagiotis Mertikopoulos, Georgios Piliouras, and Xiao Wang, “AdaGrad Avoids Saddle Points“
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Insu Han (Yale), Mike Gartrell, Elvis Dohmatob (Meta AI Research), Amin Karbasi (Yale), “Scalable MCMC Sampling for Nonsymmetric Determinantal Point Processes“.
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COLT 2022
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Mohammad Reza Karimi, Ya-Ping Hsieh, Panagiotis Mertikopoulos, Andreas Krause, “The Dynamics of Riemannian Robbins-Monro Algorithms“
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Foundations and Trends in Machine Learning
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Thomas Nédelec, Clément Calauzènes, Vianney Perchet, Nourredine El Karoui, “Online Learning in Repeated Auctions”
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Operation Research
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Thomas Nédelec, Clément Calauzènes, Vianney Perchet, Nourredine El Karoui, “Revenue-Maximizing Auctions: a bidder’s standpoint”
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Mathematics of Operations Research
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Benoit Duvocelle, Panagiotis Mertikopoulos, Mathias Staudigl, Dries Vermeulen, “Multi-agent online learning in time-varying games“
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ICASSP 2022
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Farah Cherfaoui, Hachem Kadri, Liva Ralaivola, “Scalable ridge Leverage score sampling for the Nyström method”, https://hal-amu.archives-ouvertes.fr/hal-03597111/document
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ALT 2022
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Etienne Boursier, Vianney Perchet, Marco Scarsini “Social Learning in Non-Stationary Environments”, https://arxiv.org/pdf/2007.09996.pdf
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Evrard Garcelon, Kamalika Chaudhuri, @Vianney Perchet, Matteo Pirotta “Privacy Amplification via Shuffling for Linear Contextual Bandits”,
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EUSIPCO 2022
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Pierre Palud, Pierre Chainais, Franck Le Petit, Emeric Bron, Pierre-Antoine Thouvenin, Maxime Vono, “Mixture of noises and sampling of non-log-concave posterior distributions”
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UAI 2022
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Rosanna Turrisi, Rémi Flamary, Alain Rakotomamonjy Massimiliano Pontil, “Multi-source Domain Adaptation via Weighted Joint Distributions Optimal Transport”
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AISTATS 2022
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Alain Rakotomamonjy, Rémi Flamary, Gilles Gasso, Joseph Salmon, Convergent Working Set Algorithm for Lasso with Non-Convex Sparse Regularizers
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Louis Faury, Marc Abeille, Kwang-Sung Jun, Clément Calauzènes, Jointly Efficient and Optimal Algorithms for Logistic Bandits
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ICLR 2022
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Matthieu Kirchmeyer, Alain Rakotomamonjy, Emmanuel de Bezenac, Patrick Gallinari, “Mapping conditional distributions for domain adaptation under generalized target shift”, https://arxiv.org/pdf/2110.15057.pdf
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Jérémie DONA, Marie Déchelle, Marina Levy, Patrick Gallinari, Constrained Physical-Statistics Models for Dynamical System Identification and Prediction, https://openreview.net/pdf?id=gbe1zHyA73
- Insu Han, @Mike Gartrell , Jennifer Gillenwater, Elvis Dohmatob, and Amin Karbasi. Scalable Sampling for Nonsymmetric Determinantal Point Processes.
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