University of Cambridge > Talks.cam > Applied and Computational Analysis > PDE continuum limits for prediction with expert advice

PDE continuum limits for prediction with expert advice

Add to your list(s) Download to your calendar using vCal

  • UserJeff Calder (University of Minnesota)
  • ClockThursday 06 June 2019, 15:00-16:00
  • HouseMR 14.

If you have a question about this talk, please contact Matthew Thorpe.

Prediction with expert advice refers to a class of machine learning problems that is concerned with how to optimally combine advice from multiple experts whose prediction qualities may vary greatly. We study a stock prediction problem with history-dependent experts and an adversarial (worst-case) market, posing the problem as a repeated two-player game. We prove that when the game is played for a long time, the discrete value function converges in the continuum to the solution of a nonlinear parabolic partial differential equation (PDE). This allows us to identify asymptotically optimal strategies for the player and market.

This talk is part of the Applied and Computational Analysis series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.

 

© 2006-2019 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity