Artificial Intelligence and Discrete Optimization

February 27 - March 3, 2023

Schedule

All times in this Schedule are Pacific Time (PT)

Monday, February 27, 2023

Morning Session
8:00 - 8:55 Check-In/Breakfast (Hosted by IPAM)
8:55 - 9:00 Welcome & Opening Remarks: Dean Miguel García-Garibay (Dean of Physical Sciences, UCLA) and Dima Shlyakhtenko (Director, IPAM)
9:00 - 9:50
10:00 - 10:15 Break
10:15 - 11:05
Bistra Dilkina (University of Southern California (USC))

 

11:15 - 11:30 Break
11:30 - 12:20
12:30 - 2:30 Lunch (on your own)

Afternoon Session
2:30 - 3:20
3:30 - 3:50 Break
3:50 - 4:40
Xavier Bresson (National University of Singapore)

Learning to Untangle Genome Assembly Graphs
PDF Presentation
4:45 - 5:20 Lightning Poster Session
5:20 - 6:30 Poster Session & Reception (Hosted by IPAM)

Tuesday, February 28, 2023

Morning Session
8:00 - 9:00 Check-In/Breakfast (Hosted by IPAM)
9:00 - 9:50
Yuandong Tian (Artificial Intelligence Center)

AI-guided nonlinear optimization for real-world problems
PDF Presentation
10:00 - 10:15 Break
10:15 - 11:05
11:15 - 11:30 Break
11:30 - 12:20
Thomas Laurent (Loyola Marymount University)

Feature Learning and Generalization on a Discrete Data Model

12:30 - 2:30 Lunch (on your own)

Afternoon Session
2:30 - 3:20
3:30 - 3:50 Break
3:50 - 4:40

Wednesday, March 1, 2023

Morning Session
8:00 - 9:00 Check-In/Breakfast (Hosted by IPAM)
9:00 - 9:50
Pascal Van Hentenryck (Georgia Institute of Technology)

The Fusion of Machine Learning and Optimization

10:00 - 10:15 Break
10:15 - 11:05
Bartolomeo Stellato (Princeton University)

Learning for Decision-Making Under Uncertainty

11:15 - 11:30 Break
11:30 - 12:20
12:30 - 2:00 Lunch (on your own)

Afternoon Session
2:00 - 2:50
Louis-Martin Rousseau (École Polytechnique de Montréal)

Combining Machine Learning and Optimization for efficient healthcare delivery
PDF Presentation
3:00 - 3:15 Break
3:15 - 4:05
Timo Berthold (Technische Universität Berlin)

Machine Learning inside MIP solvers

4:30 - 5:20

Thursday, March 2, 2023

Morning Session
8:00 - 9:00 Check-In/Breakfast (Hosted by IPAM)
9:00 - 9:50
Stefanie Jegelka (Massachusetts Institute of Technology)

Two aspects of learning algorithms: generalization under shifts and loss functions
PDF Presentation
10:00 - 10:15 Break
10:15 - 11:05
11:15 - 11:30 Break
11:30 - 12:20
12:30 - 2:00 Lunch (on your own)

Afternoon Session
2:00 - 2:50
Elias Khalil (University of Toronto)

Neur2SP: Neural Two-Stage Stochastic Programming


Friday, March 3, 2023

Morning Session
8:00 - 9:00 Check-In/Breakfast (Hosted by IPAM)
9:00 - 9:50
Rahul Mazumder (Massachusetts Institute of Technology)

 

10:00 - 10:15 Break
10:15 - 11:05
Paul Grigas (University of California, Berkeley (UC Berkeley))

Offline and Online Learning for Contextual Stochastic Optimization

11:15 - 11:30 Break
11:30 - 12:20