Selective Sampling Based Efficient Classifier Representation in Distributed Learning

Communication is a bottleneck for many distributed machine learning problems with large data sets. One effective approach is to exchange the set of good classifiers among the learners. The key challenge in such an approach is how to represent the set of good classifiers, which can be viewed as a sou... View More