We consider the problem of detecting anomalies in high arity categorical datasets. In most applications, anomalies are defined as data points that are 'abnormal'. Quite ...
This paper describes the experiments of the State University of New York at Buffalo in TREC 13. We participated in the Genomics track and submitted official runs to the Adhoc retri...
Miguel E. Ruiz, Munirathnam Srikanth, Rohini K. Sr...
This paper describes an efficient approach to image annotation. It ranked first on the recent scene categorization track of the ImagEVAL1 benchmark. We show how homogeneous globa...
Feature ranking is a fundamental machine learning task with various applications, including feature selection and decision tree learning. We describe and analyze a new feature ran...
Subordinate-level categorization typically rests on establishing salient distinctions between part-level characteristics of objects, in contrast to basic-level categorization, whe...
Ryan Farrell, Om Oza, Ning Zhang, Vlad I. Morariu,...