@inproceedings{daume10aoml,
  author =       {Avishek Saha and Piyush Rai and Hal {Daum\'e III} and Suresh Venkatasubramanian},
  title =        {Active Online Multitask Learning},
  booktitle =    {ICML 2010 Workshop on Budgeted Learning (Budget)},
  year =         {2010},
  address =      {Haifa, Israel},
  abstract = {
    In this paper, we propose an online multitask
    learning framework where the weight
    vectors are updated in an adaptive fashion
    based on inter-task relatedness. Our work
    is in contrast with the earlier work on online
    multitask learning (Cavallanti et al.,
    2008) where the authors use a fixed interaction
    matrix of tasks to derive (fixed) update
    rules for all the tasks. In this work,
    we propose to update this interaction matrix
    itself in an adaptive fashion so that
    the weight vector updates are no longer
    fixed but are instead adaptive. Our framework
    can be extended to an active learning
    setting where the informativeness of an
    incoming instance across all the tasks can
    be evaluated using this adaptive interaction
    matrix. Empirical results on standardized
    datasets show improved performance
    in terms of accuracy, label complexity and
    number of mistakes made.
  },
  keywords = {ml},
  tagline = {We present a simple perceptron-like algorithm for active learning in an online, domain adaptation setting.  Theory and experiments, both.},
}