Manifold learning methods are promising data analysis tools. However, if we locate a new test sample on the manifold, we have to find its embedding by making use of the learned e...
Testing reachability between nodes in a graph is a well-known problem with many important applications, including knowledge representation, program analysis, and more recently, bi...
Existing work on inference detection for database systems mainly employ functional dependencies in the database schema to detect inferences. It has been noticed that analyzing the...
A hash table is a representation of a set in a linear size data structure that supports constanttime membership queries. We show how to construct a hash table for any given set of...
The nearest neighbor (NN) classifier is well suited for generic object recognition. However, it requires storing the complete training data, and classification time is linear in ...
Ferid Bajramovic, Frank Mattern, Nicholas Butko, J...