Information-theoretic clustering aims to exploit information theoretic measures as the clustering criteria. A common practice on this topic is so-called INFO-K-means, which perfor...
Abstract. Median clustering extends popular neural data analysis methods such as the self-organizing map or neural gas to general data structures given by a dissimilarity matrix on...
Barbara Hammer, Alexander Hasenfuss, Fabrice Rossi
The open nature of collaborative recommender systems allows attackers who inject biased profile data to have a significant impact on the recommendations produced. Standard memory-...
The effectiveness of many existing high-dimensional indexing structures is limited to specific types of queries and workloads. For example, while the Pyramid technique and the iMi...
Robustness analysis research has shown that conventional memory-based recommender systems are very susceptible to malicious profile-injection attacks. A number of attack models h...