ABSTRACT. Estimating a non-uniformly sampled function from a set of learning points is a classical regression problem. Kernel methods have been widely used in this context, but eve...
Background: Sequence-derived structural and physicochemical descriptors have frequently been used in machine learning prediction of protein functional families, thus there is a ne...
Serene A. K. Ong, Hong Huang Lin, Yu Zong Chen, Ze...
Context trees are a popular and effective tool for tasks such as compression, sequential prediction, and language modeling. We present an algebraic perspective of context trees for...
Harald Ganzinger, Robert Nieuwenhuis, Pilar Nivela
Maximum margin clustering (MMC) has recently attracted considerable interests in both the data mining and machine learning communities. It first projects data samples to a kernel...
Automatic image annotation is a promising solution to enable semantic image retrieval via keywords. In this paper, we propose a multi-level approach to annotate the semantics of n...