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Showing papers from Mila, Université de Montréal & Samsung SAIL Montreal Show all papers

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NeurIPS 2026Montreal Institute for Learning U Montreal, MilaGoogle DeepMind, MilaMila, Université de Montréal &amSamsung - SAIT AI Lal MontrealAutoML & architecture search

Layerwise LQR for Geometry-Aware Optimization of Deep Networks

Layerwise LQR frames deep network preconditioners as LQR problems to learn scalable structured inverse preconditioners preserving cross-layer geometry, improving optimization dynamics with modest overhead.

Simon Dufort-Labbé, Pierre-Luc Bacon, Razvan Pascanu, Simon Lacoste-Julien and 1 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 9 of 20 reviewers recommend it
lenient 2/5
medium 6/10
strict 1/5
71%Highly rated
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NeurIPS 2026Mila - U. of MontrealMilaMila, Université de Montréal &amAutoML & architecture search

Position: Adopt Constraints Over Fixed Penalties in Deep Learning

Fixed weighted penalties poorly enforce hard deep learning constraints; use constrained formulations directly instead of scalarized surrogates.

Juan Ramirez, Seyed Meraj Hashemizadehaghda, Simon Lacoste-Julien

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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7/20 AI panelreviewers recommend it

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AI panel: 7 of 20 reviewers recommend it
lenient 4/5
medium 3/10
strict 0/5