The k-means algorithm is the method of choice for clustering large-scale data sets and it performs exceedingly well in practice. Most of the theoretical work is restricted to the c...
Conventional similarity metrics used to sustain diversity in evolving populations are not well suited to sequential decision tasks. Genotypes and phenotypic structure are poor pre...
We designed an interactive visual workspace, MediaGLOW, that supports users in organizing personal and shared photo collections. The system interactively places photos with a spri...
Andreas Girgensohn, Frank M. Shipman III, Lynn Wil...
It is shown that structural similarity between proteins can be decided well with much less information than what is used in common similarity measures. The full C representation c...
Online information services have grown too large for users to navigate without the help of automated tools such as collaborative filtering, which makes recommendations to users ba...
In many Web search applications, similarities between objects of one type (say, queries) can be affected by the similarities between their interrelated objects of another type (sa...
Information theoretic based measures form a fundamental class of similarity measures for comparing clusterings, beside the class of pair-counting based and set-matching based meas...
We investigate techniques for analysis and retrieval of object trajectories in a two or three dimensional space. Such kind of data usually contain a great amount of noise, that ma...
Michail Vlachos, Dimitrios Gunopulos, George Kolli...
Multi-target tracking requires locating the targets and labeling their identities. The latter is a challenge when many targets, with indistinct appearances, frequently occlude one...
Peter Nillius, Josephine Sullivan, Stefan Carlsson