TWiki> Ziebart Web>Research (2016-04-24, Main.bziebart)EditAttach

Research

Adversarial prediction: Approximating our training data and optimizing over the exact performance measure to provide greater flexibility for:
  • Learning under covariate shift (input distribution bias) and active learning;
  • Cost-sensitive classification and inductive optimization of univariate performance measures;
  • Learning to optimize for F-measure, discounted cumulative gain, and other multivariate performance measures; and
  • Structured prediction problems over sequences, trees, graphs, etc.
Inverse optimal control: Using maximum entropy structured prediction techniques to forecast future human behavior for intelligent robotics and vehicle navigation applications.
Topic revision: r6 - 2016-04-24 - 16:36:07 - Main.bziebart
 
Copyright 2016 The Board of Trustees
of the University of Illinois.webmaster@cs.uic.edu
WISEST
Helping Women Faculty Advance
Funded by NSF