In spite of the many decades of progress in database research, surprisingly scientists in the life sciences community still struggle with inefficient and awkward tools for queryin...
Traditional Markov network structure learning algorithms perform a search for globally useful features. However, these algorithms are often slow and prone to finding local optima d...
Reducing the number of labeled examples required to learn accurate prediction models is an important problem in structured output prediction. In this paper we propose a new transd...
This paper addresses exact learning of Bayesian network structure from data and expert's knowledge based on score functions that are decomposable. First, it describes useful ...
Abstract. The nearest neighbor and the perceptron algorithms are intuitively motivated by the aims to exploit the “cluster” and “linear separation” structure of the data to...