We propose an efficient sampling based outlier detection method for large high-dimensional data. Our method consists of two phases. In the first phase, we combine a "sampling...
Timothy de Vries, Sanjay Chawla, Pei Sun, Gia Vinh...
Motivated by applications in computer graphics, visualization, and scienti c computation, we study the computational complexity of the following problem: Given a set S of n points...
If the dataset available to machine learning results from cluster sampling (e.g. patients from a sample of hospital wards), the usual cross-validation error rate estimate can lead...
We give simple randomized incremental algorithms for computing the k-level in an arrangement of n lines in the plane or in an arrangement of n planes in R3. The expected running ti...
In this paper, we study the optimal way of distributing sensors in a random field to minimize the estimation distortion. We show that this problem is equivalent to certain proble...