Artificial Intelligence and Discrete Optimization - IPAM

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

08:00-08:55
Check-In/Breakfast (Hosted by IPAM)
08:55-09:00
Welcome & Opening Remarks: Dean Miguel García-Garibay (Dean of Physical Sciences, UCLA) and Dima Shlyakhtenko (Director, IPAM)
09:00-09:50
Andrea Lodi (Cornell University)
Continuous cutting plane algorithms in integer programming
10:00-10:15
Break
10:15-11:05
Bistra Dilkina (University of Southern California (USC))
Machine learning for MIP solving
11:15-11:30
Break
11:30-12:20
Vinod Nair (Google Brain )
Remote Talk: Restricted Boltzmann Machines for Maximum Satisfiability

Afternoon Session

12:30-14:30
Lunch (on your own)
14:30-15:20
Matej Balog (DeepMind)
AlphaTensor: Discovering faster matrix multiplication algorithms with RL
15:30-15:50
Break
15:50-16:40
Xavier Bresson (National University of Singapore)
Learning to Untangle Genome Assembly Graphs
16:45-17:20
Lightning Poster Session
17:20-18:30
Poster Session & Reception (Hosted by IPAM)

Tuesday, February 28, 2023

Morning Session

08:00-09:00
Check-In/Breakfast (Hosted by IPAM)
09:00-09:50
Yuandong Tian (Artificial Intelligence Center)
AI-guided nonlinear optimization for real-world problems
10:00-10:15
Break
10:15-11:05
Ellen Vitercik (Stanford University)
Leveraging Reviews: Learning to Price with Buyer and Seller Uncertainty
11:15-11:30
Break
11:30-12:20
Thomas Laurent (Loyola Marymount University)
Feature Learning and Generalization on a Discrete Data Model

Afternoon Session

12:30-14:30
Lunch (on your own)
14:30-15:20
Segev Wasserkug (IBM Research - Israel)
Democratizing Optimization Modeling: Status, Challenges, and Future Directions
15:30-15:50
Break
15:50-16:40
Priya Donti (Cornell University)
Remote Talk: Optimization-in-the-loop AI for energy and climate

Wednesday, March 1, 2023

Morning Session

08:00-09:00
Check-In/Breakfast (Hosted by IPAM)
09:00-09:50
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
Phebe Vayanos (University of Southern California (USC))
Integer optimization for predictive and prescriptive analytics in high stakes domains

Afternoon Session

12:30-14:00
Lunch (on your own)
14:00-14:50
Louis-Martin Rousseau (École Polytechnique de Montréal)
Combining Machine Learning and Optimization for efficient healthcare delivery
15:00-15:15
Break
15:15-16:05
Timo Berthold (Technische Universität Berlin)
Machine Learning inside MIP solvers
16:30-17:20
Hamsa Bastani (University of Pennsylvania)
Remote Talk: Decision-Aware Learning for Global Health Supply Chains

Thursday, March 2, 2023

Morning Session

08:00-09:00
Check-In/Breakfast (Hosted by IPAM)
09:00-09:50
Stefanie Jegelka (Massachusetts Institute of Technology)
Two aspects of learning algorithms: generalization under shifts and loss functions
10:00-10:15
Break
10:15-11:05
Tias Guns (KU Leuven )
Learning from user and environment in combinatorial optimisation
11:15-11:30
Break
11:30-12:20
Petar Veličković (DeepMind Technologies)
Reasoning Algorithmically: from Toy Experiments to AGI Modules

Afternoon Session

12:30-14:00
Lunch (on your own)
14:00-14:50
Elias Khalil (University of Toronto)
Neur2SP: Neural Two-Stage Stochastic Programming

Friday, March 3, 2023

Morning Session

08:00-09:00
Check-In/Breakfast (Hosted by IPAM)
09:00-09:50
Rahul Mazumder (Massachusetts Institute of Technology)
(Discrete) Optimization-aided structured learning at Scale: Some examples
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
Tina Eliassi-Rad (Northeastern University)
Two Optimization Problems on Graphs and Why ML-based Optimization Underperforms
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