We present some novel machine learning techniques for the identification of subcategorization information for verbs in Czech. We compare three different statistical techniques app...
Searching approximate nearest neighbors in large scale high dimensional data set has been a challenging problem. This paper presents a novel and fast algorithm for learning binary...
The goal of sufficient dimension reduction in supervised learning is to find the lowdimensional subspace of input features that is `sufficient' for predicting output values. ...
Incomplete data is a common drawback that machine learning techniques need to deal with when solving real-life classification tasks. One of the most popular procedures for solving ...
In this article, we describe a feature selection algorithm which can automatically find relevant features for multiple instance learning. Multiple instance learning is considered a...