@COMMENT This file was generated by bib2html.pl <http://www.cs.cmu.edu/~pfr/misc_software/index.html#bib2html> version 0.90
@COMMENT written by Patrick Riley <http://www.cs.cmu.edu/~pfr>
@COMMENT This file came from Peter Stone's publication pages at
@COMMENT http://www.cs.utexas.edu/~pstone/papers
@InProceedings{CoLLAs22-Liu,
  author = {Bo Liu and Qiang Liu and Peter Stone},
  title = {Continual Learning and Private Unlearning},
  booktitle = {Proceedings of the 1st Conference on Lifelong Learning Agents (CoLLA)},
  location = {Montreal, Canada},
  month = {August},
  year = {2022},
  abstract = { 
As intelligent agents become autonomous over longer periods of time, they may eventually become lifelong counterparts to specific people. If so, it may be common for a user to want the
agent to master a task temporarily but later on to forget the task due to privacy concerns. However enabling an agent to forget privately what the user specified without degrading the rest of
the learned knowledge is a challenging problem. With the aim of addressing this challenge,
this paper formalizes this continual learning and private unlearning (CLPU) problem. The paper further introduces a straightforward but exactly private solution, CLPU-DER++, as the first
step towards solving the CLPU problem, along with a set of carefully designed benchmark problems to evaluate the effectiveness of the proposed solution.
  },
}