A low-effort data mining approach to labeling network event records in a WLAN is proposed. The problem being addressed is often observed in an AI and data mining strategy to netwo...
Taghi M. Khoshgoftaar, Chris Seiffert, Naeem Seliy...
Abstract—Transactional memory promises to generalize transactional programming to mainstream languages and data structures. The purported benefit of transactions is that they ar...
Learning a sequence classifier means learning to predict a sequence of output tags based on a set of input data items. For example, recognizing that a handwritten word is "ca...
In this work we try to bridge the gap often encountered by researchers who find themselves with few or no labeled examples from their desired target domain, yet still have access ...
Abstract. We propose an algorithm for Sparse Bayesian Classification for multi-class problems using Automatic Relevance Determination(ARD). Unlike other approaches which treat mult...