In this article we compare the performance of various machine learning algorithms on the task of constructing word-sense disambiguation rules from data. The distinguishing characte...
Georgios Paliouras, Vangelis Karkaletsis, Ion Andr...
Hierarchical reinforcement learning (RL) is a general framework which studies how to exploit the structure of actions and tasks to accelerate policy learning in large domains. Pri...
In this paper we evaluate two methods for key estimation from polyphonic audio recordings. Our goal is to compare between a strategy using a cognition-inspired model and several m...
The ratio of two probability densities can be used for solving various machine learning tasks such as covariate shift adaptation (importance sampling), outlier detection (likeliho...
We studied the effects of pair programming in a team context on productivity, defects, design quality, knowledge transfer and enjoyment of work. Randomly formed three pair program...