The task of object identification occurs when integrating information from multiple websites. The same data objects can exist in inconsistent text formats across sites, making it ...
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...
This paper describes a local ensemble kernel learning technique to recognize/classify objects from a large number of diverse categories. Due to the possibly large intraclass featu...
We present the machine learning framework that we are developing, in order to support explorative search for non-trivial linguistic configurations in low-density languages (langua...
We present methods for inferring the cost of interrupting users based on multiple streams of events including information generated by interactions with computing devices, visual ...