We study the combinatorics of cross-validation based AUC estimation unde...
The goal of recommender systems is to help users find useful items from ...
Game recommendation is an important application of recommender systems.
...
Pairwise learning corresponds to the supervised learning setting where t...
In machine learning one often assumes the data are independent when
eval...
This paper proposes a novel method for learning highly nonlinear,
multiv...
Many machine learning problems can be formulated as predicting labels fo...
Receiver operating characteristic (ROC) analysis is widely used for
eval...
Maximizing product use is a central goal of many businesses, which makes...
Kronecker product kernel provides the standard approach in the kernel me...
We consider the problem of learning regression functions from pairwise d...
Enzyme sequences and structures are routinely used in the biological sci...
In domains like bioinformatics, information retrieval and social network...
Driven by a large number of potential applications in areas like
bioinfo...