Covariate shift is a situation in supervised learning where training and test inputs follow different distributions even though the functional relation remains unchanged. A common...
Yuta Tsuboi, Hisashi Kashima, Shohei Hido, Steffen...
The rigid all-versus-all adjacency required by a maximal biclique for its two vertex sets is extremely vulnerable to missing data. In the past, several types of quasi-bicliques ha...
In this paper, we study online algorithms when the input is not chosen adversarially, but consists of draws from some given probability distribution. While this model has been stu...
The integration of sophisticated inference-based techniques into natural language processing applications first requires a reliable method of encoding the predicate-argument struc...
Spoken Language Understanding (SLU) addresses the problem of extracting semantic meaning conveyed in an utterance. The traditional knowledge-based approach to this problem is very...