Random sampling is a well-known technique for approximate processing of large datasets. We introduce a set of algorithms for incremental maintenance of large random samples on seco...
This work reduces the computational requirements of the additive noise steganalysis presented by Harmsen and Pearlman. The additive noise model assumes that the stegoimage is crea...
Jeremiah J. Harmsen, Kevin D. Bowers, William A. P...
In many real-world domains, supervised learning requires a large number of training examples. In this paper, we describe an active learning method that uses a committee of learner...
Themost costly aspect of gathering information over the Internet is that of transferring data over the networkto answer the user’s query. Wemaketwo contributions in this paperth...
Image filtering is often applied as a post-process to Monte Carlo generated pictures, in order to reduce noise. In this paper we present an algorithm based on density estimation t...