We present a novel algorithm for agglomerative hierarchical clustering based on evaluating marginal likelihoods of a probabilistic model. This algorithm has several advantages ove...
High-throughput, data-directed computational protocols for Structural Genomics (or Proteomics) are required in order to evaluate the protein products of genes for structure and fu...
This paper links two a priori different topics, group testing and traitor tracing. Group testing, as an instantiation of a compressed sensing problem over binary data, is indeed e...
Keyword queries over structured databases are notoriously ambiguous. No single interpretation of a keyword query can satisfy all users, and multiple interpretations may yield over...
Elena Demidova, Peter Fankhauser, Xuan Zhou, Wolfg...
Matrix factorization (MF) models have proved efficient and well scalable for collaborative filtering (CF) problems. Many researchers also present the probabilistic interpretation o...