We propose a novel kernel regression algorithm which takes into account order preferences on unlabeled data. Such preferences have the form that point x1 has a larger target value...
Previous Multiple Kernel Learning approaches (MKL) employ different kernels by their linear combination. Though some improvements have been achieved over methods using single kerne...
Abstract—Over the past few years, wireless sensor networks received tremendous attention for monitoring physical phenomena, such as the temperature field in a given region. Appl...
In this work, a generalized method for learning from sequence of unlabelled data points based on unsupervised order-preserving regression is proposed. Sequence learning is a funda...
The preference model introduced in this paper gives a natural framework and a principled solution for a broad class of supervised learning problems with structured predictions, su...