Abstract. We develop a generic framework for deriving linear-size problem kernels for NP-hard problems on planar graphs. We demonstrate the usefulness of our framework in several c...
We introduce a new approach to analyzing click logs by examining both the documents that are clicked and those that are bypassed--documents returned higher in the ordering of the ...
Atish Das Sarma, Sreenivas Gollapudi, Samuel Ieong
Naive Bayes and logistic regression perform well in different regimes. While the former is a very simple generative model which is efficient to train and performs well empirically...
Subgroup discovery aims at finding subsets of a population whose class distribution is significantly different from the overall distribution. It has previously predominantly been...
A serious drawback of kernel methods, and Support Vector Machines (SVM) in particular, is the difficulty in choosing a suitable kernel function for a given dataset. One of the appr...
Huyen Do, Alexandros Kalousis, Adam Woznica, Melan...