A learning problem that has only recently gained attention in the machine learning community is that of learning a classifier from group probabilities. It is a learning task that ...
Accurate, well-calibrated estimates of class membership probabilities are needed in many supervised learning applications, in particular when a cost-sensitive decision must be mad...
In this paper, we introduce a new approach to dialect recognition which relies on the hypothesis that certain phones are realized differently across dialects. Given a speaker'...
When building a classifier from clean training data for a particular test environment, knowledge about the environmental noise and channel should be taken into account. We propos...
Kevin Jamieson, Maya R. Gupta, Eric Swanson, Hyrum...
Class membership probability estimates are important for many applications of data mining in which classification outputs are combined with other sources of information for decisi...