Supercomputer architects strive to maximize the performance of scientific applications. Unfortunately, the large, unwieldy nature of most scientific applications has lead to the...
Richard C. Murphy, Arun Rodrigues, Peter M. Kogge,...
In this paper we introduce a framework for privacypreserving distributed computation that is practical for many real-world applications. The framework is called Peers for Privacy ...
Yitao Duan, NetEase Youdao, John Canny, Justin Z. ...
Background: Gene expression profiling has become a useful biological resource in recent years, and it plays an important role in a broad range of areas in biology. The raw gene ex...
Abstract. We formulate a robust method using Expectation Maximization (EM) to address the problem of dense photometric stereo. Previous approaches using Markov Random Fields (MRF) ...
In this paper we embed evolutionary computation into statistical learning theory. First, we outline the connection between large margin optimization and statistical learning and s...