EPFL CIS NeurIPS 2021 Mirror Event

The Conference on Neural Information Processing Systems (NeurIPS) is the main machine learning conference.
While the conference being highly selective, EPFL researchers have more than 60 papers accepted for presentation at the conference, more than any other continental Europe institutions. However, due to the current pandemic, the conference will be done entirely remotely instead of in-person.
We have thus decided to organize a local mid-scale event in SwissTech Convention Center, on the EPFL campus, and to invite all the EPFL researchers and students who have a paper accepted at NeurIPS this year to join us on Monday, December 6, for an in-person poster session, and extended the invitation to all Swiss institutions. We do believe that local events such as this one are also very useful to reduce our travel impact while creating opportunities for informal discussion and creation of new ideas.
The conference will give the occasion to all EPFL students and researchers with accepted papers at NeurIPS 2021 to present their works, and to all students and researchers interested in machine learning research to connect and discuss science during this one-day event.
Organisation committee:
Prof. Florent Krzakala, EPFL (IdePhics Lab.)
Prof. Nicolas Flammarion, EPFL (TML Lab.)
Prof. Lenka Zdeborova, EPFL (SPOC Lab.)
Program
09:00-10:00 Welcome coffee
10:00-11:00 Spotlight Talks: 9 x Spotlight session (5 mins each)
- Decentralized Learning in Online Queuing Systems, Etienne Boursier
- Learning Gaussian Mixtures with Generalized Linear Models: Precise Asymptotics in High-dimensions Bruno Loureiro
- Uniform Sampling over Episode Difficulty, Séb Arnold
- Sequential Algorithms for Testing Closeness of Distributions, Aadil Oufkir
- Prototypical Cross-Attention Networks for Multiple Object Tracking and Segmentation, Lei Ke
- Repulsive Deep Ensembles are Bayesian, Vincent Fortuin
- On the Power of Differentiable Learning versus PAC and SQ Learning, Emmanuel Abbe
- Credit Assignment in Neural Networks through Deep Feedback Control, Alexander Meulemans, Matilde Tristany Farinha
- Precise characterization of the prior predictive
distribution of deep ReLU networks, Lorenzo Noci, Gregor Bachmann
11:00-12:00 poster sessions (see listing below)
12h00-14:00 lunch on campus
14:00-15:00 Oral Session (25mins each)
- Stability and Deviation Optimal Risk Bounds with Convergence Rate O(1/n), Nikita Zhivotovskiy
- A Continuized View on Nesterov Acceleration for Stochastic Gradient Descent and Randomized Gossip, Raphael Berthier
15:00-17:00 Coffee & poster sessions
Poster list
1* RobustBench: a standardized adversarial robustness benchmark Other NeurIPS tracks (e.g. competition, benchmark…) Francesco Croce, Maksym Andriushchenko, Vikash Sehwag, Edoardo Debenedetti, Nicolas Flammarion, Mung Chiang, Prateek Mittal, Matthias Hein
2* Decentralized Learning in Online Queuing Systems Spotlight Flore Sentenac, Etienne Boursier, Vianney Perchet
3* Score-based Generative Neural Networks for Large-Scale Optimal Transport Poster Max Daniels, Tyler Maunu, Paul Hand
4* Generalization error rates in kernel regression : the crossover from the noiseless to the noisy regime Poster Hugo Cui, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
5*Learning curves of generic features maps for realistic datasets with a teacher-student model Poster Bruno Loureiro, Cedric Gerbelot, Hugo Cui, Sebastian Goldt, Florent Krzakala, Marc Mezard, Lenka Zdeborová
6* Learning Gaussian Mixtures with Generalized Linear Models: Precise Asymptotics in High-dimensions Spotlight Bruno Loureiro, Gabriele Sicuro, Cedric Gerbelot, Alessandro Pacco, Florent Krzakala, Lenka Zdeborova
7* What can linearized neural networks actually say about generalization? Poster Guillermo Ortiz-Jimenez, Seyed-Mohsen Moosavi-Dezfooli, Pascal Frossard
8*Last iterate convergence of SGD for Least-Squares in the Interpolation regime Poster Aditya Varre, Loucas Pillaud-Vivien, Nicolas Flammarion
9* Interpreting Language Models Through Knowledge Graph Extraction Spotlight Vinitra Swamy, Angelika Romanou, Martin Jaggi
10* Neural Design Space Exploration Other NeurIPS tracks (e.g. competition, benchmark…) Wei Jiang, Richard Lee Davis, Kevin Kim, Pierre Dillenbourg
11* Locality defeats the curse of dimensionality in convolutional teacher-student scenarios Poster A. Favero, F. Cagnetta, M. Wyart
12* An Improved Analysis of Gradient Tracking for Decentralized Machine Learning Poster Anastasia Koloskova, Tao Lin, Sebastian Stich
13* RelaySum for Decentralized Deep Learning on Heterogeneous Data Poster Thijs Vogels, Lie He, Anastasia Koloskova, Tao Lin, Sai Praneeth Karimireddy, Sebastian U. Stich, Martin Jaggi
14* Learning Transferable Adversarial Perturbations Poster Krishna Kanth Nakka and Mathieu Salzmann
15* Efficient and Local Parallel Random Walks Poster Michael Kapralov, Silvio Lattanzi, Navid Nouri, Jakab Tardos
16* Stability and Deviation Optimal Risk Bounds with Convergence Rate O(1/n) Oral Yegor Klochkov, Nikita Zhivotovskiy
17* Model, sample, and epoch-wise descents: exact solution of gradient flow in the random feature model Poster Antoine Bodin & Nicolas Macris
18* Relative stability toward diffeomorphisms indicates performance in deep nets Poster Leonardo Petrini, Alessandro Favero, Mario Geiger, Matthieu Wyart
19* TTT++: When Does Self-Supervised Test-Time Training Fail or Thrive? Poster Yuejiang Liu, Parth Kothari, Bastien Germain van Delft, Baptiste Bellot-Gurlet, Taylor Mordan, Alexandre Alahi
20* Implicit Bias of SGD for Diagonal Linear Networks: a Provable Benefit of Stochasticity. Poster Scott Pesme, Loucas Pillaud-Vivien, Nicolas Flammarion
21* A Continuized View on Nesterov Acceleration for Stochastic Gradient Descent and Randomized Gossip Oral M. Even, R. Berthier, F. Bach, N. Flammarion, P. Gaillard, H. Hendrikx, L. Massoulié, A. Taylor
22* Unfirom Sampling over Episode Difficulty Spotlight Sébastien M. R. Arnold, Guneet S. Dhillon, Avinash Ravichandran, Stefano Soatto
23* Distilling Image Classifiers in Object Detectors Poster Shuxuan Guo, Jose M. Alvarez, Mathieu Salzmann
24* Robust Inverse Reinforcement Learning under Transition Dynamics Mismatch Poster Luca Viano, Yu-Ting Huang, Kamalaruban Parameswaran, Adrian Weller, Volkan Cevher
25* A first-order primal-dual method with adaptivity to local smoothness Poster Maria Vladarean, Yura Malitsky, Volkan Cevher
26* Collaborative Learning in the Jungle (Decentralized, Byzantine, Heterogeneous, Asynchronous and Nonconvex Learning) Poster El Mahdi El Mhamdi, Sadegh Farhadkhani, Rachid Guerraoui, Arsany Guirguis, Lê-Nguyên Hoang, Sébastien Rouault
27* Conditional Generation Using Polynomial Expansions Poster Grigorios Chrysos, Markos Georgopoulos, Yannis Panagakis
28* Sequential Algorithms for Testing Closeness of Distributions Spotlight Omar Fawzi, Nicolas Flammarion, Aurélien Garivier, Aadil Oufkir
29* Breaking the centralized barrier for cross-device federated learning Poster Sai Praneeth Karimireddy, Martin Jaggi, Satyen Kale, Mehryar Mohri, Sashank Reddi, Sebastian Stich, Ananda Theertha Suresh
30* SQALER: scaling question answering by decoupling multi-hop and logical reasoning Poster Mattia Atzeni, Jasmina Bogojeska, Andreas Loukas
31* Prototypical Cross-Attention Networks for Multiple Object Tracking and Segmentation Spotlight Lei Ke, Xia Li, Martin Danelljan, Yu-Wing Tai, Chi-Keung Tang, Fisher Yu
32* Making the most of your day: online learning for optimal allocation of time Poster Etienne Boursier, Tristan Garrec, Vianney Perchet, Marco Scarsini
33* Self-Supervised Representation Learning on Neural Network Weights for Model Characteristic Prediction Poster Konstantin Schürholt, Dimche Kostadinov, Damian Borth
34* On the Bias-Variance-Cost Tradeoff of Stochastic Optimization Poster Yifan Hu, Xin Chen, Niao He
35* Local plasticity rules can learn deep representations using self-supervised contrastive predictions Poster Bernd Illing, Jean Ventura, Guillaume Bellec, Wulfram Gerstner
36* Partition and Code: learning how to compress graphs Poster Giorgos Bouritsas, Andreas Loukas, Nikolaos Karalias, Michael M. Bronstein
37* Fitting summary statistics of neural data with a differentiable spiking network simulator Poster Guillaume Bellec, Shuqi Wang, Alireza Modirshanechi, Johanni Brea, Wulfram Gerstner
38* Learning where to learn: Gradient sparsity in meta and continual learning Poster Johannes Von Oswald, Dominic Zhao, Seijin Kobayashi, Simon Schug, Massimo Caccia, Nicolas Zucchet, Joao Sacramento
39* Information Directed Reward Learning for Reinforcement Learning Poster David Lindner, Matteo Turchetta, Sebastian Tschiatschek, Kamil Ciosek, and Andreas Krause
40* Prototypical Cross-Attention Networks for Multiple Object Tracking and Segmentation Spotlight Lei Ke, Xia Li, Martin Danelljan, Yu-Wing Tai, Chi-Keung Tang, Fisher Yu
41* STORM+: Fully Adaptive SGD with Recursive Momentum for Nonconvex Optimization Poster Kfir Y. Levy, Ali Kavis, Volkan Cevher
42* Repulsive Deep Ensembles are Bayesian Spotlight Francesco D’Angelo, Vincent Fortuin
43* Credit assignment in neural networks through Deep Feedback Control Spotlight Alexander Meulemans, Matilde Tristany Farinha, Javier García Ordóñez, Pau Vilimelis Aceituno, João Sacramento, Benjamin F. Grewe
44* The staircase property: how hierarchical structure can guide deep learning Poster E. Abbe, E. Boix-Adsera, M. Brenner, G. Bresler, D. Nagarj
45* On the Power of Differentiable Learning versus PAC and SQ Learning Spotlight E. Abbe, P. Kamath, E. Malach, C. Sandon, N. Srebro
46* Predicting future myocardial infarction from angiographies with deep learning Other NeurIPS tracks (e.g. competition, benchmark…) Dorina Thanou1 Ortal Senouf1 Omar Raita1 Emmanuel Abbé1 Pascal Frossard1 Farhang Aminfar2 Denise Auberson2 Nicolas Dayer2 David Meier2 Mattia Pagnoni2 Olivier Muller2 Stéphane Fournier2 Thabodhan Mahendiran2
47* Subquadratic Overparameterization for Shallow Neural Networks Poster Chaehwan Song, Ali Ramezani-Kebrya, Thomas Pethick, Armin Eftekhari, Volkan Cevher
48* Nearly-Tight and Oblivious Algorithms for Explainable Clustering Poster Buddhima Gamlath · Xinrui Jia · Adam Polak · Ola Svensson
49* Risk-averse Heteroscedastic Bayesian Optimization Poster Anastasia_Makarova , Ilnura Usmanova, Ilija Bogunovic, Andreas Krause
*50 Convergence of adaptive algorithms for constrained weakly convex
optimization, Ahmet Alacaoglu, Yura Malitsky, Volkan Cevher
*51 Sifting through the noise: Universal first-order methods for
stochastic variational inequalities, K. Antonakopoulos, T. Pethick, A.
Kavis, P. Mertikopoulos and V. Cevher
*52 Tree in Tree: from Decision Trees to Decision Graphs, Bingzhao
Zhu, Mahsa Shoaran
*53 DNN-based Topology Optimisation: Spatial Invariance and Neural
Tangent Kernel, Benjamin Dupuis, Arthur Jacot
*54 Precise characterization of the prior predictive distribution of
deep ReLU networks, Lorenzo Noci, Gregor Bachmann, Kevin Roth,
Sebastian Nowozin, Thomas Hofmann
*55 Interpolation can hurt robust generalization even when there is no noise, Konstantin Donhauser, Alexandru Tifrea, Michael Aerni, Reinhard Heckel, Fanny Yang
* 56 The Effect of the Intrinsic Dimension on the Generalization of Quadratic Classifiers,Fabian Latorre, Leello Tadesse Dadi, Paul Rolland, Volkan Cevher
* 57 Recursive Bayesian Networks: Generalising and Unifying Probabilistic Context-Free Grammars and Dynamic Bayesian Networks, Robert Lieck & Martin Rohrmeier
Replay
Part I
Part 2










