We propose a framework MIC (Multiple Inclusion Criterion) for learning sparse models based on the information theoretic Minimum Description Length (MDL) principle. MIC provides an...
Paramveer S. Dhillon, Dean P. Foster, Lyle H. Unga...
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
When search is against structured documents, it is beneficial to extract information from user queries in a format that is consistent with the backend data structure. As one step...
—We present a computer-aided detection (CAD) system for computed tomography colonography that orders the polyps according to clinical relevance. The CAD system consists of two st...
Vincent Frans van Ravesteijn, Cees van Wijk, Frans...
We consider the problem of wide-area large-scale text search over a peer-to-peer infrastructure. A wide-area search infrastructure with billions of documents and millions of searc...
Vijay Gopalakrishnan, Bobby Bhattacharjee, Peter J...