Schedule

The schedule is tentative and will be updated as the semester progresses.

Date	Topic	Readings	Assignment(s)
9/1	Course overview and introduction
9/3	Background on online algorithms and competitive analysis		Problem set assigned
9/8	Ski rental with predictions I	• Improving Online Algorithms via ML Predictions • (Optional) Optimal Robustness-Consistency Trade-offs for Learning-Augmented Online Algorithms	Reading response due on Monday, 9/7
9/10	Ski rental with predictions II
9/15	Metrical task systems I	• Online metric algorithms with untrusted predictions • (Optional) Optimal robustness-consistency tradeoffs for learning-augmented metrical task systems	Reading response due on Monday, 9/14
9/17	Metrical task systems II		Problem set due
9/22	Speeding up matching algorithms I	• Faster Matchings via Learned Duals	Reading response due on Monday, 9/21
9/24	Speeding up matching algorithms II
9/29	Learning predictions from data I	• Learning Predictions for Algorithms with Predictions • (Optional) Customizing ML Predictions For Online Algorithms • (Optional) Learning Online Algorithms with Distributional Advice	Reading response due on Monday, 9/28
10/1	Learning predictions from data II
10/6	Uncertainty quantification for algorithms with predictions I	• Online algorithms with uncertainty-quantified predictions • (Optional) Algorithms with calibrated machine learning predictions	Reading response due on Monday, 10/5
10/8	Uncertainty quantification for algorithms with predictions II		Project proposal due
10/13	TBA
10/15	TBA
10/20	TBA
10/22	Fall break, no class
10/27	TBA
10/29	TBA
11/3	TBA
11/5	Mid-semester project updates
11/10	TBA
11/12	TBA
11/17	Student paper presentations
11/19	Student paper presentations
11/24	Thanksgiving break, no class
11/26	Thanksgiving break, no class
12/1	Student paper presentations
12/3	Student paper presentations
12/8	Student paper presentations
12/10	Student paper presentations
12/15, 9am-12pm	Final project presentations		Project writeup due by end of day