In this paper, we give a simple scheme for identifying approximate frequent items over a sliding window of size n. Our scheme is deterministic and does not make any assumption on ...
We address evaluation of image understanding and retrieval large scale image data in the context of three evaluation projects. The first project is a comprehensive strategy for e...
Keiji Yanai, Nikhil V. Shirahatti, Prasad Gabbur, ...
We describe a slightly subexponential time algorithm for learning parity functions in the presence of random classification noise, a problem closely related to several cryptograph...
This paper addresses the problem of identifying redundant data in large-scale service-oriented information systems. Specifically, the paper puts forward an automated method to pi...
Mining cluster evolution from multiple correlated time-varying text corpora is important in exploratory text analytics. In this paper, we propose an approach called evolutionary h...