Gaussian graphical models are of great interest in statistical learning. Because the conditional independencies between different nodes correspond to zero entries in the inverse c...
We introduce a new algorithm for binary classification in the selective sampling protocol. Our algorithm uses Regularized Least Squares (RLS) as base classifier, and for this reas...
In this paper, we attempt to improve the effectiveness and the efficiency of query-dependent link-based ranking algorithms such as HITS, MAX and SALSA. All these ranking algorith...
This paper introduces the notion of temporally constrained ranked retrieval, which, given a query and a time constraint, produces the best possible ranked list within the specifi...
Based on rank-1 update, Sparse Bayesian Learning Algorithm (SBLA) is proposed. SBLA has the advantages of low complexity and high sparseness, being very suitable for large scale pr...