Contact Us

Give us a call or drop by anytime, we endeavor to answer all inquiries within 24 hours.


Find us

PO Box 16122 Collins Street West Victoria, Australia

Email us /

Phone support

Phone: + (066) 0760 0260 / + (057) 0760 0560

Loading Events

« All Events

  • This event has passed.

Towards the Statistically Principled Design of ML Algorithms | Frederic Koehler

March 6 @ 10:00 am

Event Series Event Series (See All)

What are the optimal algorithms for learning from data? Have we found them already, or are better ones out there to be discovered? Making these questions precise, and answering them, requires taking on the mathematically deep interplay between statistical and computational constraints. It also requires reconciling our theoretical toolbox with surprising new phenomena arising from practice, which seem to violate conventional rules of thumb regarding algorithm and model design. I will discuss progress along these lines: in terms of designing new algorithms for basic learning problems, controlling generalization in large statistical models, and understanding key statistical questions for generative modeling.

Bio: Frederic is currently a Motwani Postdoctoral Fellow in the Department of Computer Science at Stanford University. He was previously a research fellow at the Simons Institute, and before that received his PHD in Mathematics and Statistics.


March 6
10:00 am
Event Category:


SDSC, The Auditorium
9500 Gilman Drive
La Jolla, CA United States


HDSI General