Question classification is very important for question answering. This paper presents our research work on automatic question classification through machine learning approaches. W...
This paper explores unexpected results that lie at the intersection of two common themes in the KDD community: large datasets and the goal of building compact models. Experiments ...
We consider the problem of learning Gaussian multiresolution (MR) models in which data are only available at the finest scale and the coarser, hidden variables serve both to captu...
Myung Jin Choi, Venkat Chandrasekaran, Alan S. Wil...
—Known covert channel based on splitting algorithms in Medium Access Control (MAC) protocols requires the receiver’s knowledge of the sender’s identity. In this paper we pres...
Gradient Boosting and bagging applied to regressors can reduce the error due to bias and variance respectively. Alternatively, Stochastic Gradient Boosting (SGB) and Iterated Baggi...