Schedule

Thursday, May 16, 2024

Time	Event
9:30 - 10:00	Welcome + Breakfast
10:00 - 10:45	Brice Huang: Capacity threshold for the Ising perceptron
10:45 - 11:30	Elisabetta Cornacchia: Learning Parities with Neural Networks: Initialization and Curriculum
11:30 - 1:30	Lunch break + Poster Session
1:30 - 2:15	Libin Zhu: Spikes in the training loss of SGD and their impact on generalization through feature learning
2:15 - 3:00	Yizhe Zhu: Random feature and kernel regression with relaxed data assumptions
3:00 - 3:30	Break + Discussion
3:30 - 4:15	Jason Gaitonde: Sample-Efficient Linear Regression with Self-Selection Bias
4:15 - 6:30	Poster Session + Reception (Reception starts at 5:30 PM)

Time	Event
9:30 - 10:00	Breakfast
10:00 - 10:45	Theodor Misiakiewicz: On the complexity of differentiable learning on product measures
10:45 - 11:30	Kangjie Zhou: New algorithms for Ising Perceptron
11:30 - 1:30	Lunch break + Discussion
1:30 - 2:30	Panel Discussion
2:30 - 2:40	Break
2:40 - 3:25	Jingfeng Wu: Reimagining Gradient Descent: Large Stepsize, Oscillation, and Acceleration
3:25 - 4:10	Gal Katzhendler: Multicover: Towards Efficient Induction of Sample Complexity
4:10 - 6:00	Walk to beach Google map