We propose a new approach for outlier detection, based on a new ranking measure that focuses on the question of whether a point is “important” for its nearest neighbors; using our notations low cumulative rank implies the point is central. For instance, a point centrally located in a cluster has relatively low cumulative sum of ranks because it is among the nearest neighbors of its own nearest ...

Dimensionality reduction methods are of interest in applications such as content based image and video retrieval. In large multimedia databases, it may not be practical to search through the entire database in order to retrieve the nearest neighbors of a query. Good data structures for similarity search and indexing are needed, and the existing data structures do not scale well for the high dim...

Risk-based assessment in pipe conditions mainly focuses on prioritizing the most critical assets by evaluating risk of failure. This paper's goal is to classify a comprehensive rating model which obtained based series pipe, external, and hydraulic characteristics that are identified for proposed methodology. The traditional manual method assessing sewage structural takes long time. By building ...

Conditional t-SNE (ct-SNE) is a recent extension to that allows removal of known cluster information from the embedding, obtain visualization revealing structure beyond label information. This useful, for example, when one wants factor out unwanted differences between set classes. We show ct-SNE fails in many realistic settings, namely if data well clustered over labels original high-dimensiona...