Mining for outliers in sequential databases is crucial to forward appropriate analysis of data. Therefore, many approaches for the discovery of such anomalies have been proposed. ...
Classifying the endgame positions in Chess can be challenging for humans and is known to be a difficult task in machine learning. An evolutionary algorithm would seem to be the ide...
In this paper the application of reinforcement learning to Tetris is investigated, particulary the idea of temporal difference learning is applied to estimate the state value funct...
The Named Entity Recognition (NER) task has been garnering significant attention in NLP as it helps improve the performance of many natural language processing applications. In th...
Code-switching is an interesting linguistic phenomenon commonly observed in highly bilingual communities. It consists of mixing languages in the same conversational event. This pa...
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
We discuss the use in machine learning of a general type of convex optimisation problem known as semi-definite programming (SDP) [1]. We intend to argue that SDP’s arise quite n...
In the past, we have succesfully used machine learning approaches for sentiment analysis. In the course of those experiments, we observed that our machine learning method, althoug...
In this paper, we report on the design of a part-of-speech-tagset for Wolof and on the creation of a semi-automatically annotated gold standard. The main motivation for this resou...
Cheikh M. Bamba Dione, Jonas Kuhn, Sina Zarrie&szl...
Automatically translating natural language into machine-readable instructions is one of major interesting and challenging tasks in Natural Language (NL) Processing. This problem c...