In this paper we apply Conformal Prediction (CP) to the k-Nearest Neighbours Regression (k-NNR) algorithm and propose ways of extending the typical nonconformity measure used for ...
Harris Papadopoulos, Vladimir Vovk, Alexander Gamm...
Learning from imbalanced data occurs frequently in many machine learning applications. One positive example to thousands of negative instances is common in scientific applications...
Abstract. Machine learning can be utilized to build models that predict the runtime of search algorithms for hard combinatorial problems. Such empirical hardness models have previo...
Frank Hutter, Youssef Hamadi, Holger H. Hoos, Kevi...
In competitive domains, the knowledge about the opponent can give players a clear advantage. This idea lead us in the past to propose an approach to acquire models of opponents, ba...
Background: One-dimensional protein structures such as secondary structures or contact numbers are useful for three-dimensional structure prediction and helpful for intuitive unde...