Abstract. We introduce a nonparametric model for sensitivity estimation which relies on generating points similar to the prediction point using its k nearest neighbors. Unlike most...
Despite its simplicity, the naive Bayes classifier has surprised machine learning researchers by exhibiting good performance on a variety of learning problems. Encouraged by thes...
In this paper we introduce Structured Local Predictors (SLP) – A new formulation that considers the image labelling problem from a structured learning point of view. SLP are loc...
Multiple kernel learning (MKL) uses a weighted combination of kernels where the weight of each kernel is optimized during training. However, MKL assigns the same weight to a kerne...
In the paper, we investigate the use of reinforcement learning in CBR for estimating and managing a legacy case base for playing the game of Tetris. Each case corresponds to a loc...