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How to allow deep learning on your data without revealing your data
Presenter
- Sanjeev Arora
February 25, 2021
IPAM
Task-driven Network Discovery via Deep Reinforcement Learning on Embedded Spaces
Presenter
- Tina Eliassi-Rad
February 25, 2021
IPAM
Combining Reinforcement Learning and Constraint Programming for Combinatorial Optimization
Presenter
- Louis-Martin Rousseau
February 25, 2021
IPAM
Task structure and generalization in graph neural networks
Presenter
- Stefanie Jegelka
February 25, 2021
IPAM
Decision-focused learning: integrating downstream combinatorics in ML
Presenter
- Bistra Dilkina
February 25, 2021
IPAM
Discrete Optimal Transport by Parallel Network Simplex
Presenter
- Stefano Gualandi
February 25, 2021
IPAM
Fast semidefinite programming for (differentiable) combinatorial optimization
Presenter
- Zico Kolter
February 25, 2021
IPAM
How much data is sufficient to learn high-performing algorithms?
Presenter
- Ellen Vitercik
February 24, 2021
IPAM
Ecole: A Gym-like Library for Machine Learning in Combinatorial Optimization Solvers
Presenter
- Maxime Gasse
February 24, 2021
IPAM
Deep Learning for Combinatorial Optimization: count your flops and make your flops count!
Presenter
- Wouter Kool
February 24, 2021
IPAM
Exact Combinatorial Optimization with Graph Convolutional Neural Networks
Presenter
- Laurent Charlin
February 24, 2021
IPAM