MTL MLOpt
Montréal Machine Learning and Optimization (MTL MLOpt) is a group of researchers living and working in Montréal.Our research loosely spans topics in machine learning and mathematical optimization. Many of our members are affiliated with the Mila, where we also held our physical meetings (in pre-apocalyptic times). The group includes researchers from the University of Montréal, McGill, Google Brain, Samsung SAIT AI Lab (SAIL) Montreal, Facebook AI Research Montréal (FAIR) and Microsoft Research Montréal.
We hold public and internal meetings. The public meetings are a seminar with guest lecturers from around the world. Our public meetings are open for everyone to attend. Our internal meetings typically comprise of a presentation of a member’s latest work, followed by discussion which often leads to productive collaborations.
- 57:31
- 3 ай бұрын
Elliot Paquette - Random matrix theory for high dimensional optim, and application to scaling laws
- 1:02:07
- 3 ай бұрын
Courtney Paquette - Hitting the High-D(imensional) Notes: An ODE for SGD learning dynamics
- 1:13:03
- 3 ай бұрын
Gauthier Gidel - On the stability of iterative retraining of generative models on their own data
- 1:12:54
- 3 ай бұрын
Adam Oberman - Theoretical insights into self-supervised feature representation learning
- 1:13:31
- 3 ай бұрын
Jose Gallego-Posada - PI controllers for updating Lagrange multipliers in constrained optimization
- 1:15:45
- 3 ай бұрын
Motahareh Sohrabi - Weight-Sharing Regularization
- 1:09:05
- 3 ай бұрын
Louis Fournier - Can Forward Gradient Match Backpropagation ?
- 1:10:07
- 2 жыл бұрын
Dimitris Papailiopoulos - Learning is Pruning
- 41:34
- 2 жыл бұрын
Mark Sellke - A Universal Law of robustness via Isoperimetry
- 1:18:41
- 2 жыл бұрын
Lenka Zdeborova - Insights on gradient based algorithms in high-dimensional non-convex optimization
- 1:05:48
- 2 жыл бұрын
Jelena Diakonikolas - Structure in Min-Max Optimization
- 1:17:54
- 2 жыл бұрын
Aaron Defazio - Adventures in optimization for large-scale deep learning
- 1:17:50
- 2 жыл бұрын
Panayotis Mertikopoulos - Games, Dynamics and Min-Max Optimization
- 56:11
- 2 жыл бұрын
Lorenzo Rosasco - An Implicit Tour of Regularization
- 57:34
- 3 жыл бұрын
Anastasios Kyrillidis - Distributed Learning of Neural Networks using Independent Subnet Training
- 1:16:18
- 3 жыл бұрын
Nicolas Loizou - SGD for Modern Machine Learning: Practical Variants and Convergence Guarantees&q...
- 1:09:14
- 3 жыл бұрын
Robert M. Gower - New viewpoints, variants and convergence theory for stochastic Polyak step-sizes
- 1:18:54
- 3 жыл бұрын
Ashia Wilson - Variational Perspectives on Machine Learning
- 1:17:28
- 3 жыл бұрын
Kamalika Chaudhuri - Challenges in Reliable Machine Learning
- 1:04:31
- 3 жыл бұрын
Sebastien Bubeck - A law of robustness for two-layers neural networks
- 54:48
- 3 жыл бұрын
Rachel Ward - Weighted Optimization: Better Generalization via Smoother Interpolation
- 1:20:01
- 4 жыл бұрын
Constantinos Daskalakis - The Complexity of Min-Max Optimization
- 1:04:27
- 4 жыл бұрын
Francis Bach - On the effectiveness of Richardson Extrapolation in Machine Learning
- 1:12:22
- 4 жыл бұрын
Peter Richtarik - On Second Order Methods and Randomness
- 53:57
- 4 жыл бұрын
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