We consider the problem of reducing the dimensionality of labeled data for classification. Unfortunately, the optimal approach of finding the low-dimensional projection with minim...
The recent proliferation of crowd computing initiatives on the web calls for smarter methodologies and tools to annotate, query and explore repositories. There is the need for scal...
Roberto Mirizzi, Azzurra Ragone, Tommaso Di Noia, ...
We analyze and improve low rank representation (LRR), the state-of-the-art algorithm for subspace segmentation of data. We prove that for the noiseless case, the optimization mode...
Nonnegative Matrix Factorization (NMF) approximates a given data matrix as a product of two low rank nonnegative matrices, usually by minimizing the L2 or the KL distance between ...
Abstract. We are presenting a coherent framework for XQuery processing that incorporates IR-style approximate matching and allows the ordering of results by their relevance score. ...