Research

Hi! PARIS at NeurIPS 2021

24 research papers accepted at the conference on Neural Information Processing Systems (NeurIPS) 2021

Hi! PARIS is pleased to present the work of its researchers and professors at the 35th Conference on Neural Information Processing Systems (NeurIPS) being held this week (Dec 6-14, 2021).

For this edition, 24 publications were accepted by the reviewers for their significant contribution in the field of machine learning. The NeurIPS conference is world-renowned as one of the largest and most important machine learning conferences in the world.

The accepted papers cover a range of topics of AI. HEC Paris and several schools of Institut Polytechnique de Paris are represented.

Congratulations to our Professors and Researchers!

École polytechnique, Institut Polytechnique de Paris: Aymeric Dieuleveut, Rémi Flamary, Eric Moulines, Charles Ollion, Constantin Philippenko, Erwan Scornet, Achille Thin

ENSAE Paris, Institut Polytechnique de Paris: Arya Akhavan, Etienne Boursier, Cristina Butucea, Evrard Garcelon, Yann Issartel, Olga Klopp, Vianney Perchet, Flore Sentenac, Alexandre Tsybakov

HEC Paris: Julien Grand-Clément

Inria Saclay: Alexandre Gramfort, Federica Granese, Pedro L. C. Rodrigues, Marine Le Morvan, Thomas Moreau, Catuscia Palamidessi, Hugo Richard, Bertrand Thirion, Gael Varoquaux

Telecom Paris, Institut Polytechnique de Paris: Florence D’Alché-Buc, Kamélia Daudel, Pavlo Mozharovskyi, Nathan Noiry, Jayneel Parekh, Gaël Richard, Milad Sefidgaran

Telecom Sud Paris, Institut Polytechnique de Paris: Randal Douc, Yazid Janati, Sylvain Le Corff

Here is the complete list of NeurIPS publications for Professors and Researchers in Hi! PARIS:
  1. DOCTOR: A Simple Method for Detecting Misclassification Errors
    Federica Granese, Marco Romanelli, Daniele Gorla, Catuscia Palamidessi, Pablo Piantanida [link] SPOTLIGHT
  2. What’s a good imputation to predict with missing values?
    Marine Le Morvan, Julie Josse, Erwan Scornet, Gael Varoquaux [link] SPOTLIGHT
  3. Decentralized Learning in Online Queuing Systems
    Flore Sentenac, Etienne Boursier, Vianney Perchet [link] SPOTLIGHT
  4. Online Sign Identification: Minimization of the Number of Errors in Thresholding Bandits
    Reda Ouhamma, Rémy Degenne, Vianney Perchet, Pierre Gaillard [link] SPOTLIGHT
  5. Disentangling Identifiable Features from Noisy Data with Structured Nonlinear ICA
    Hermanni Hälvä, Sylvain Le Corff, Luc Lehéricy, Jonathan So, Yongjie Zhu, Elisabeth Gassiat, Aapo Hyvarinen [link]
  6. Preserved central model for faster bidirectional compression in distributed settings
    Constantin Philippenko, Aymeric Dieuleveut [link]
  7. A New Theoretical Framework for Fast and Accurate Online Decision-Making
    Nicolò Cesa-Bianchi, Tom Cesari, Yishay Mansour, Vianney Perchet [link]
  8. Conic Blackwell Algorithm: Parameter-Free Convex-Concave Saddle-Point Solving
    Julien Grand-Clément, Christian Kroer [link]
  9. Distributed Zero-Order Optimization under Adversarial Noise
    Arya Akhavan, Massimiliano Pontil, Alexandre Tsybakov [link]
  10. Local Differential Privacy for Regret Minimization in Reinforcement Learning
    Evrard Garcelon, Vianney Perchet, Ciara Pike-Burke, Matteo Pirotta [link]
  11. Making the most of your day: online learning for optimal allocation of time
    Etienne Boursier, Tristan Garrec, Vianney Perchet, Marco Scarsini [link]
  12. NEO: Non Equilibrium Sampling on the Orbits of a Deterministic Transform
    Achille Thin, Yazid Janati El Idrissi, Sylvain Le Corff, Charles Ollion, Eric Moulines, Arnaud Doucet, Alain Durmus, Christian Robert [link]
  13. Optimality of variational inference for stochasticblock model with missing links
    Solenne Gaucher, Olga Klopp [link]
  14. Online Matching in Sparse Random Graphs: Non-Asymptotic Performances of Greedy Algorithm
    Nathan Noiry, Vianney Perchet, Flore Sentenac [link]
  15. Unbalanced Optimal Transport through Non-negative Penalized Linear Regression
    Laetitia Chapel, Rémi Flamary, Haoran Wu, Cédric Févotte, Gilles Gasso [link]
  16. A Framework to Learn with Interpretation
    Jayneel Parekh, Pavlo Mozharovskyi, Florence D’Alché-Buc [link]
  17. Stochastic Online Linear Regression: the Forward Algorithm to Replace Ridge Reda Ouhamma, Odalric-Ambrym Maillard, Vianney Perchet [link]
  18. Locally differentially private estimation of functionals of discrete distributions
    Cristina Butucea, Yann Issartel [link]
  19. Heavy Tails in SGD and Compressibility of Overparametrized Neural Networks
    Melih Barsbey, Seyedmilad Sefidgaran, Murat A. Erdogdu, Gaël Richard, Umut Simsekli [link]
  20. Federated-EM with heterogeneity mitigation and variance reduction
    Aymeric Dieuleveut, Gersende Fort, Eric Moulines, Geneviève Robin [link]
  21. Tight High Probability Bounds for Linear Stochastic Approximation with Fixed Stepsize
    Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov, Kevin Scaman, Hoi-To Wai [link]
  22. Shared Independent Component Analysis for Multi-Subject Neuroimaging
    Hugo Richard, Pierre Ablin, Bertrand Thirion, Alexandre Gramfort, Aapo Hyvarinen [link]
  23. HNPE: Leveraging Global Parameters for Neural Posterior Estimation
    Pedro Luiz Coelho Rodrigues, Thomas Moreau, Gilles Louppe, Alexandre Gramfort [link]
  24. Mixture weights optimisation for Alpha-Divergence Variational Inference
    Kamélia Daudel, Randal Douc [link]