Spring 2026

Meeting Schedule

We will meet weekly on Mondays, 11:00AM-01:00PM, usually in HSPH 2-426.

Date	Room	Topic	Reading	Presenter
26th Jan.	2-426		Bach (2024): Ch. 1, 2
2nd Feb.	2-426		connections with research
9th Feb.	2-426		Bach (2024): Ch. 3, 4
16th Feb.	2-426		connections with research
23rd Feb.	2-426		Bach (2024): Ch. 5, 6
2nd Mar.	2-426		connections with research
9th Mar.	2-426		Bach (2024): Ch. 7, 8
16th Mar.	2-426		connections with research
23rd Mar.	2-426		Bach (2024): Ch. 9, 10
30th Mar.	2-426		connections with research
6th Apr.	2-426		Bach (2024): Ch. 11, 12
13th Apr.	2-426		connections with research
20th Apr.	2-426		tbd
27th Apr.	2-426		connections with research
4th May	2-426		tbd
11th May	2-426		connections with research

In the Spring 2026 term, we will continue to discuss topics in statistical learning theory and statistical machine learning, with material to be drawn from the texts Bach (2024), Bickel and Doksum (2015), and Duchi (2024) (see details below).

• Bach (2024): Ch. 1 (mathematical preliminaries), 2 (supervised learning), 3 (linear least-squares), 4 (empirical risk minimization), 5 (optimization for machine learning), 6 (local averaging methods), 7 (kernel methods), 8 (sparse methods), 9 (neural networks), 10 (ensemble learning), 11 (from online learning to bandits), 12 (over-parametrized models)
• Bickel and Doksum (2015): Ch. 7 (tools for asymptotic analysis), 9 (inference in semi-parametric models), 12 (prediction and machine learning)
• Duchi (2024): Ch. 2 (basics of information theory), 4 (concentration inequalities), 5 (generalization and stability), 8 (minimax lower bounds),

References

Bach, Francis. 2024. Learning Theory from First Principles. https://www.di.ens.fr/%7Efbach/ltfp_book.pdf.

Bickel, Peter J, and Kjell A Doksum. 2015. Mathematical Statistics: Basic Ideas and Selected Topics, Volume II. CRC Press. https://doi.org/10.1201/b19822.

Duchi, John. 2024. Statistics and Information Theory. https://web.stanford.edu/class/stats311/lecture-notes.pdf.