SAIL Montreal @ ICML 2023

2023-07-23T00:00:00+00:00

SAIL Montreal is happy to have a strong presence at ICML 2023. Our office manager Geneviève Bernard will be present on site along with some of our research scientist who are happy to have a chat with you.

What is SAIL Montreal?

SAIL Montreal (SAIT AI Lab Montreal) is a recently-established academic-style research lab (in close collaboration with Mila) from Samsung whose mission is to push the boundaries of AI with SAIT and Mila through open fundamental research. Headed by Simon Lacoste-Julien, professor in computer science at Université de Montréal and co-founding member of Mila, SAIL is located in Mila's corporate space at the heart of the Montreal AI ecosystem nearby Borealis AI, Meta AI, Microsoft Research and others where an open collaborative environment is encouraged.

Accepted papers at ICML 2023

Click the links for more information on these papers (requires ICML registration). Underlined authors are SAIL-affiliated, * denotes equal contribution between authors.

Oral

Difference of submodular minimization via DC programming [openreview] [code]
Marwa El Halabi, George Orfanides, Tim Hoheisel
Oral presentation: Oral C1 supervised learning Thu 27 Jul 3 p.m. HST — 4:30 p.m. HST
Exhibit Hall 1 #643, Wed 26 Jul 11 a.m. HST — 12:30 p.m. HST

Tuesday

Unlocking Slot Attention by Changing Optimal Transport Costs [openreview] [code]
Yan Zhang*, David W Zhang*, Simon Lacoste-Julien, Gertjan J. Burghouts, Cees G. M. Snoek
Exhibit Hall 1 #111, Tue 25 Jul 11 a.m. HST — 1:30 p.m. HST
Can We Scale Transformers to Predict Parameters of Diverse ImageNet Models? [openreview] [code]
Boris Knyazev, Doha Hwang, Simon Lacoste-Julien
Exhibit Hall 1 #808, Wed 26 Jul 11 a.m. HST — 12:30 p.m. HST

Wednesday

Fairness in Streaming Submodular Maximization over a Matroid Constraint [openreview] [code]
Marwa El Halabi*, Ashkan Norouzi-Fard*, Jakab Tardos*, Jakub Tarnawski*, Federico Fusco*
Exhibit Hall 1 #642, Wed 26 Jul 11 a.m. HST — 12:30 p.m. HST
Difference of submodular minimization via DC programming [openreview] [code]
Marwa El Halabi, George Orfanides, Tim Hoheisel
Oral presentation: Oral C1 supervised learning Thu 27 Jul 3 p.m. HST — 4:30 p.m. HST
Exhibit Hall 1 #643, Wed 26 Jul 11 a.m. HST — 12:30 p.m. HST
CrossSplit: Mitigating Label Noise Memorization through Data Splitting [openreview]
Jihye Kim, Aristide Baratin, Yan Zhang, Simon Lacoste-Julien
Exhibit Hall 1 #210, Wed 26 Jul 11 a.m. HST — 12:30 p.m. HST
Fast Online Node Labelling with Local and Global Consistency [openreview]
Baojian Zhou, Yifan Sun, Reza Babanezhad
Exhibit Hall 1 #723, Wed 26 Jul 2 p.m. HST — 3:30 p.m. HST
Target-based Surrogates for Stochastic Optimization [openreview]
Jonathon W. Lavington, Sharan Vaswani, Reza Babanezhad, Mark Schmidt, Nicolas Le Roux
Exhibit Hall 1 #438, Wed 26 Jul 2 p.m. HST — 3:30 p.m. HST

Thursday

Equivariance with Learned Canonicalization Functions [openreview]
Sékou-Oumar Kaba*, Arnab Kumar Mondal*, Yan Zhang, Yoshua Bengio, Siamak Ravanbakhsh
Exhibit Hall 1 #127, Thu 27 Jul 1:30 p.m. HST — 3 p.m. HST

Finding us

The following research scientists will be available in-person at ICML 2023:

Come find us at our posters, or send us an email to arrange something individual. You can find the full list of people on our main website.

Workshops

We also have some workshop papers:

Friday

Pretrained Language Models to Solve Graph Tasks in Natural Language
Frederik Wenkel, Guy Wolf, Boris Knyazev
ICML Workshop on Structured Probabilistic Inference & Generative Modeling
Learning to Optimize with Recurrent Hierarchical Transformers
Abhinav Moudgil, Boris Knyazev, Guillaume Lajoie, Eugene Belilovsky
ICML Workshop on New Frontiers in Learning, Control, and Dynamical Systems
Neural Networks Are Graphs! Graph Neural Networks for Equivariant Processing of Neural Networks
David W. Zhang, Miltiadis Kofinas, Yan Zhang, Yunlu Chen, Gertjan J. Burghouts, Cees G. M. Snoek
ICML Workshop on Topology, Algebra, and Geometry in Data Science

Saturday

Decision-Aware Actor-Critic with Function Approximation and Theoretical Guarantees
Sharan Vaswani, Amirreza Kazemi, Reza Babanezhad, Nicolas Le Roux
ICML Workshop on Duality Principles for Modern ML

SAIL Montreal @ NeurIPS 2022

2022-11-28T00:00:00+00:00

SAIL Montreal is happy to sponsor NeurIPS 2022! We will have a booth where you can meet some of our research scientists.

What is SAIL Montreal?

SAIL Montreal (SAIT AI Lab Montreal) is a recently established academic-style research lab (in close collaboration with Mila) from Samsung whose mission is to advance our fundamental understanding of deep learning technology and its applications. Headed by Simon Lacoste-Julien, professor in computer science at Université de Montréal and co-founding member of Mila, SAIL is located in Mila's corporate space at the heart of the Montreal AI ecosystem nearby Borealis AI, FAIR, Microsoft Research and others where an open collaborative environment is encouraged.

We are hiring!

We are hiring research scientists! Scroll down on that page for more information about the position and how to apply.

Accepted papers at NeurIPS 2022

Click the links for more information on these papers (requires NeurIPS registration).

The Curse of Unrolling: Rate of Differentiating Through Optimization [arxiv]
Damien Scieur, Quentin Bertrand, Gauthier Gidel and Fabian Pedregosa
Wed 30 Nov 11:30 a.m. CST — 1 p.m. CST @ Hall J #724
Model Zoos: A Dataset of Diverse Populations of Neural Network Models [arxiv]
Konstantin Schürholt, Diyar Taskiran, Boris Knyazev, Xavier Giró-i-Nieto, Damian Borth
Wed 30 Nov 11:30 a.m. CST — 1 p.m. CST @ Hall J #1017
Hyper-Representations as Generative Models: Sampling Unseen Neural Network Weights [arxiv]
Konstantin Schürholt, Boris Knyazev, Xavier Giró-i-Nieto, Damian Borth
Thu 1 Dec 11:30 a.m. CST — 1 p.m. CST @ Hall J #605
MCVD: Masked Conditional Video Diffusion for Prediction [arxiv]
Vikram Voleti, Alexia Jolicoeur-Martineau, Christopher Pal
Thu 1 Dec 11:30 a.m. CST — 1 p.m. CST @ Hall J #921
Spotlight: Tue 6 Dec 8 p.m. CST — 8:15 p.m. CST
Data-Efficient Structured Pruning via Submodular Optimization [arxiv]
Marwa El Halabi, Suraj Srinivas, Simon Lacoste-Julien
Thu 1 Dec 11:30 a.m. CST — 1 p.m. CST @ Hall J #938

Finding us

The following research scientists will be available in-person at NeurIPS 2022:

You can find the full list of people on our main website.

Booth

Our booth will be at the Expo hall #224. Our office manager Geneviève Bernard will be there most of the time, with a rotating cast of research scientists.

Workshops

Our research scientist Alexia Jolicoeur-Martineau co-organizes the Workshop on Score-Based Methods on Friday December 2 in Room 293-294.

We also have some workshop papers:

Unlocking Slot Attention by Changing Optimal Transport Costs
Yan Zhang*, David W Zhang*, Simon Lacoste-Julien, Gertjan J. Burghouts, Cees G. M. Snoek
Poster at All Things Attention, December 2 (hybrid in-person and virtual)
Equivariance With Learned Canonicalization Functions
Sékou-Oumar Kaba*, Arnab Kumar Mondal*, Yan Zhang, Yoshua Bengio, Siamak Ravanbakhsh
Oral at Symmetry and Geometry in Neural Representations, December 3 (in-person)
Target-based Surrogates for Stochastic Optimization
J. Wilder Lavington, Sharan Vaswani, Reza Babanezhad, Mark Schmidt, Nicolas Le Roux
Poster at Optimization for Machine Learning, December 3 (in-person)
Unlocking Slot Attention by Changing Optimal Transport Costs
Yan Zhang*, David W Zhang*, Simon Lacoste-Julien, Gertjan J. Burghouts, Cees G. M. Snoek
Oral at Neuro Causal and Symbolic AI, December 9 (virtual)