Recently, privacy issues have become important in data analysis, especially when data is horizontally partitioned over several parties. In data mining, the data is typically repre...
Data anonymization techniques based on enhanced privacy principles have been the focus of intense research in the last few years. All existing methods achieving privacy principles ...
Detecting and tracking latent factors from temporal data is an important task. Most existing algorithms for latent topic detection such as Nonnegative Matrix Factorization (NMF) h...
Bin Cao, Dou Shen, Jian-Tao Sun, Xuanhui Wang, Qia...
The most basic assumption used in statistical learning theory is that training data and test data are drawn from the same underlying distribution. Unfortunately, in many applicati...
We derive categories directly from robot sensor data to address the symbol grounding problem. Unlike model-based approaches where human intuitive correspondences are sought betwee...
Daniel H. Grollman, Odest Chadwicke Jenkins, Frank...