We study the problem of estimating the best k term Fourier representation for a given frequency-sparse signal (i.e., vector) A of length N k. More explicitly, we investigate how t...
Sparse coding—that is, modelling data vectors as sparse linear combinations of basis elements—is widely used in machine learning, neuroscience, signal processing, and statisti...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
Abstract. We apply sparse Bayesian learning methods, automatic relevance determination (ARD) and predictive ARD (PARD), to Alzheimer’s disease (AD) classification to make accura...
Li Shen, Yuan Qi, Sungeun Kim, Kwangsik Nho, Jing ...
The rank and select operations over a string of length n from an alphabet of size σ have been used widely in the design of succinct data structures. In many applications, the stri...
Worms propagating in online social networking (OSN) websites have become a major security threat to both the websites and their users in recent years. Since these worms exhibit un...