Data reduction plays an important role in machine learning and pattern recognition with a high-dimensional data. In real-world applications data usually exists with hybrid formats...
In practical issues, categorical data and numerical data usually coexist, and a unified data reduction technique for hybrid data is desirable. In this paper, an information measu...
Background: Recent biological discoveries have shown that clustering large datasets is essential for better understanding biology in many areas. Spectral clustering in particular ...
Habil Zare, Parisa Shooshtari, Arvind Gupta, Ryan ...
A key component in Distributed Interactive Simulations (DIS) is the number of data packets transmitted across the connected networks. To reduce the number of packets transmitted, ...
Recommender Systems are gaining widespread acceptance in e-commerce applications to confront the information overload problem. Collaborative Filtering (CF) is a successful recommen...