Classification in imbalanced domains is a recent challenge in machine learning. We refer to imbalanced classification when data presents many examples from one class and few from ...
Occam’s razor is the principle that, given two hypotheses consistent with the observed data, the simpler one should be preferred. Many machine learning algorithms follow this pr...
The amount of readily available on-line text has reached hundreds of billions of words and continues to grow. Yet for most core natural language tasks, algorithms continue to be o...
The imprecise computation model provides the ability to cope with unpredictable workloads. However, there is no consistent way on how to terminate the computation in its early sta...
The paper studies the problem of maintaining external dynamic dictionaries with variable length keys. We introduce a new type of balanced trees, called S(b)-trees, which generaliz...