Given a sample from a probability measure with support on a submanifold in Euclidean space one can construct a neighborhood graph which can be seen as an approximation of the subm...
Matthias Hein, Jean-Yves Audibert, Ulrike von Luxb...
Closed sets have been proven successful in the context of compacted data representation for association rule learning. However, their use is mainly descriptive, dealing only with ...
Kernel Canonical Correlation Analysis (KCCA) is a method of correlating linear relationship between two variables in a kernel defined feature space. A machine learning algorithm b...
The paper focuses on the study of solving the large-scale traveling salesman problem (TSP) based on neurodynamic programming. From this perspective, two methods, temporal differenc...
Jia Ma, Tao Yang, Zeng-Guang Hou, Min Tan, Derong ...
We develop a new multiclass classification method that reduces the multiclass problem to a single binary classifier (SBC). Our method constructs the binary problem by embedding sm...