EPFL @ NeurIPS 2022

List of the EPFL accepted papers:

1. Identifiability and generalizability from multiple experts in Inverse Reinforcement Learning by Paul Rolland, Luca Viano, Norman Schuerhoff, Boris Nikolov, Volkan Cevher
2. Understanding Deep Neural Function Approximation in Reinforcement Learning via ε-Greedy Exploration by Fanghui Liu, Luca Viano, Volkan Cevher
3. No-regret learning in games with noisy feedback: Faster rates and adaptivity via learning rate separation by Yu-Guan Hsieh, Kimon Antonakopoulos, Volkan Cevher, Panayotis Mertikopoulos
4. On the Double Descent of Random Features Models Trained with SGD by Fanghui Liu, Johan Suykens, Volkan Cevher
5. A First Approach to Universal Second-Order Acceleration for Convex Minimization by Ali Kavis, Kimon Antonakopoulos, Volkan Cevher
6. Robustness in deep learning: The good (width), the bad (depth), and the ugly (initialization) by Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher
7. Sound and Complete Verification of Polynomial Networks by Elias Abad Rocamora, Mehmet Fatih Sahin, Fanghui Liu, Grigorios Chrysos, Volkan Cevher
8. Proximal Point Imitation Learning by Luca Viano, Angeliki Kamoutsi, Gergely Neu, Igor Krawczuk, Volkan Cevher
9. Extrapolation and Spectral Bias of Neural Nets with Hadamard Product: a Polynomial Net Study by Yongtao Wu, Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher
10. Generalization Properties of NAS under Activation and Skip Connection Search by Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher
11. Adaptive Stochastic Variance Reduction for Non-convex Finite-Sum Minimization by Ali Kavis, Efstration Panteleimon Skoulakis, Kimon Antonakopoulos, Leello Tadesse Dadi, Volkan Cevher
12. Learning sparse features can lead to overfitting in neural networks by Leonardo Petrini, Francesco Cagnetta, Eric Vanden-Eijnden, Matthieu Wyart
13. Low-rank lottery tickets: finding efficient low-rank neural networks via matrix differential equations by Steffen Schotthöfer, Emanuele Zangrando, Jonas Kusch, Gianluca Ceruti, Francesco Tudisco
14. Deep Bidirectional Language-Knowledge Pretraining by Michihiro Yasunaga, Antoine Bosselut, Hongyu Ren, Xikun Zhang, Christopher D Manning, Percy Liang, Jure Leskovec
15. Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks by Rodrigo Veiga, Ludovic Stephan, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
16. Subspace clustering in high-dimensions: Phase transitions & Statistical-to-Computational gap by Luca Pesce, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
17. Multi-layer State Evolution Under Random Convolutional Design by Max Daniels, Cédric Gerbelot, Florent Krzakala, Lenka Zdeborová
18. Sharper Convergence Guarantees for Asynchronous SGD for Distributed and Federated Learning by Anastasia Koloskova, Sebastian U. Stich, Martin Jaggi
19. Beyond spectral gap: The role of the topology in decentralized learning by Thijs Vogels, Hadrien Hendrikx, Martin Jaggi
20. Decentralized local stochastic extra-gradient for variational inequalities by Aleksandr Beznosikov, Pavel Dvurechensky, Anastasia Koloskova, Valentin Samokhin, Sebastian U Stich, Alexander Gasnikov
21. Gradient flow dynamics of shallow ReLU networks for square loss and orthogonal inputs by Etienne Boursier, Loucas Pillaud-Vivien, Nicolas Flammarion
22. Stochastic Second-Order Methods Provably Beat SGD For Gradient-Dominated Functions by Mohammadsaeed Masiha · Saber Salehkaleybar · Niao He · Negar Kiyavash · Patrick Thiran
23. Sharp Analysis of Stochastic Optimization under Global Kurdyka-Lojasiewicz Inequality by Jalal Etesami · Ilyas Fatkhullin · Niao He · Negar Kiyavash
24. Causal Discovery in Linear Latent Variable Models Subject to Measurement Error by Yuqin Yang · AmirEmad Ghassami · Mohamed Nafea · Negar Kiyavash · Kun Zhang · Ilya Shpitser
25. Trajectory Inference via Mean-field Langevin in Path Space by Lénaïc Chizat, Stephen Zhang, Matthieu Heitz, Geoffrey Schiebinger
26. Generalised Implicit Neural Representations by Daniele Grattarola · Pierre Vandergheynst
27. DMAP: a Distributed Morphological Attention Policy for learning to locomote with a changing body by Alberto Chiappa · Alessandro Marin Vargas · Alexander Mathis
28. On the non-universality of deep learning: quantifying the cost of symmetry by Emmanuel Abbe · Enric Boix-Adsera
29. Learning to Reason with Neural Networks: Generalization, Unseen Data and Boolean Measures by Emmanuel Abbe · Samy Bengio · Elisabetta Cornacchia · Jon Kleinberg · Aryo Lotfi · Maithra Raghu · Chiyuan Zhang
30. Kernel Attractor Networks: A Unifying Framework for Memory Modeling by Georgios Iatropoulos · Johanni Brea · Wulfram Gerstner
31. Mesoscopic modeling of hidden spiking neurons by Shuqi Wang · Valentin Schmutz · Guillaume Bellec · Wulfram Gerstner
32. Feature Learning in L2-regularized DNNs: Attraction/Repulsion and Sparsity by Arthur Jacot · Eugene Golikov · Clement Hongler · Franck Gabriel
33. Towards Consistency in Adversarial Classification by Laurent Meunier, Raphael Ettedgui, Rafael Pinot, Yann Chevaleyre, Jamal Atif
34. Neural Set Function Extensions: Learning with Discrete Functions in High Dimensions by Nikolaos Karalias, Joshua Robinson, Andreas Loukas, Stefanie Jegelka
35. Beyond Time-Average Convergence: Near-Optimal Uncoupled Online Learning via Clairvoyant Multiplicative Weights Update by Georgios Piliouras, Ryan Simm, Stratis Skoulakis
36. Contact-aware Human Motion Forecasting by Wei Mao, Miaomiao Liu, Richard Hartley, Mathieu Salzmann
37. Robust Binary Models by Pruning Randomly-initialized Networks by Chen Liu, Ziqi Zhao, Sabine Süsstrunk, Mathieu Salzmann
38. Non-Gaussian Tensor Programs by Greg Yang and Eugene Golikov
39. FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Settings by Jean Ogier du Terrail · Samy-Safwan Ayed · Edwige Cyffers · Felix Grimberg · Chaoyang He · Regis Loeb · Paul Mangold · Tanguy Marchand · Othmane Marfoq · Erum Mushtaq · Boris Muzellec · Constantin Philippenko · Santiago Silva · Maria Teleńczuk · Shadi Albarqouni · Salman Avestimehr · Aurélien Bellet · Aymeric Dieuleveut · Martin Jaggi · Sai Praneeth Karimireddy · Marco Lorenzi · Giovanni Neglia · Marc Tommasi · Mathieu Andreux
40. Task Discovery: Finding the Tasks that Neural Networks Generalize on by Andrei Atanov, Andrey Filatov, Teresa Yeo, Ajay Sohmshetty, Amir Zamir
41. PALMER: Perception-Action Loop with Memory Reorganization for Planning by Onur Beker, Mohammad Mohammadi, Amir Zamir