Abstractions and Case-Based Reasoning for Medical Course Data: Two Prognostic Applications . . . . . . . . . . . . . . . . . 23 R. Schmidt and L. Gierl Are Case-Based Reasoning and...
Abstract— We have used measurements taken on real network to enhance the performance of our radio network planning tool. A distribution learning technique is adopted to realize t...
This paper proposes a very general max-margin learning framework for distance-based clustering. To this end, it formulates clustering as a high order energy minimization problem w...
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
Abstract. Clustering data described by categorical attributes is a challenging task in data mining applications. Unlike numerical attributes, it is difficult to define a distance b...