In database query processing, actual run-time conditions (e.g., actual selectivities and actual available memory) very often differ from compile-time expectations of run-time cond...
Recommender systems (RSs) are popular tools dealing with information overload problems in eCommerce Web sites. RSs match user preferences with item representations and recommend t...
Fabiana Lorenzi, Francesco Ricci, Mara Abel, Ana L...
We consider the problem of learning a sparse multi-task regression, where the structure in the outputs can be represented as a tree with leaf nodes as outputs and internal nodes a...
When equipped with kernel functions, online learning algorithms are susceptible to the "curse of kernelization" that causes unbounded growth in the model size. To addres...
We develop an efficient learning framework to construct signal dictionaries for sparse representation by selecting the dictionary columns from multiple candidate bases. By sparse,...