We present a technique for organizing data in spatial databases with non-convex domains based on an automatic characterization using the medial-axis transform (MAT). We define a t...
Eric A. Perlman, Randal C. Burns, Michael M. Kazhd...
A common approach in machine learning is to use a large amount of labeled data to train a model. Usually this model can then only be used to classify data in the same feature spac...
Identifying information-rich subsets in high-dimensional spaces and representing them as order revealing patterns (or trends) is an important and challenging research problem in m...
—For modern scientific applications such as astrophysics, astronomy, aerography, and biology, a large amount of storage space is required because of the large-scale datasets. Dat...
Output-sensitive data structures result from preprocessing n items and are capable of reporting the items satisfying an on-line query in O(t(n) + ℓ) time, where t(n) is the cost ...