Clustering stability is an increasingly popular family of methods for performing model selection in data clustering. The basic idea is that the chosen model should be stable under...
Many online networks are measured and studied via sampling techniques, which typically collect a relatively small fraction of nodes and their associated edges. Past work in this a...
Maciej Kurant, Minas Gjoka, Yan Wang, Zack W. Almq...
In this paper, we introduce new algorithms for selecting taxon samples from large evolutionary trees, maintaining uniformity and randomness, under certain new constraints on the t...
Anupam Bhattacharjee, Zalia Shams, Kazi Zakia Sult...
Advances in data collection technologies allow accumulation of large and high dimensional datasets and provide opportunities for learning high quality classification and regression...
Most existing structure from motion (SFM) approaches for unordered images cannot handle multiple instances of the same structure in the scene. When image pairs containing differen...
Richard Roberts, Sudipta Sinha, Richard Szeliski, ...