Algorithms, Geometry and Learning

This seminar-like reading group is aimed at being in the intersection of three research areas Theoretical Computer Science, Machine Learning, Mathematics having Metric Spaces as its unifying theme. Last quarter we put more emphasis on Geometry and tried to gain understanding of mappings between metric spaces. This quarter, our emphasis will be . Of course any topic related to the general theme of the reading group would be considered.

Format: This is meant as a weekly two-hour reading group, where emphasis is on techniques and presenting the main proofs.

Contact: For questions, suggestions or to declare interest email Paris Siminelakis.

Tentative List of Topics

For a more specific list click on the topics tab.

1. Spectral Sparsification and Effective Resistances

2. Decomposing a Graph into Expanders

3. Low-stretch Spanning Trees

4. Spectral Embedding

Participants

People who have participated or contributed during at least one session.

Professors

Students