We propose preprocessing spectral clustering with b-matching to remove spurious edges in the adjacency graph prior to clustering. B-matching is a generalization of traditional maxi...
In solving complex visual learning tasks, adopting multiple descriptors to more precisely characterize the data has been a feasible way for improving performance. These representa...
Nowadays, graph-based knowledge discovery algorithms do not consider numeric attributes (they are discarded in the preprocessing step, or they are treated as alphanumeric values w...
Oscar E. Romero, Jesus A. Gonzalez, Lawrence B. Ho...
Previous studies of data-driven dependency parsing have shown that the distribution of parsing errors are correlated with theoretical properties of the models used for learning an...
Motivated by issues in machine learning and statistical pattern classification, we investigate a class cover problem (CCP) with an associated family of directed graphs--class cove...