'protected classes' in the population.

It requires a bounded domain.

However, most existing techniques focus only on overcoming CF and have no mechanism to encourage KT, and thus do not do well in KT. Although several papers have tried to deal with both CF and KT, our experiments show that they suffer from serious CF when the tasks do not have much shared knowledge.

We study the problem of online learning with primary and secondary losses.

Our approach reduces the problem into a sequence of plug-in classifier learning tasks.