We present a new unsupervised algorithm for training structured predictors that is discriminative, convex, and avoids the use of EM. The idea is to formulate an unsupervised versi...
Linli Xu, Dana F. Wilkinson, Finnegan Southey, Dal...
This work is motivated by the necessity to automate the discovery of structure in vast and evergrowing collection of relational data commonly represented as graphs, for example ge...
The diversity of computers and networks within a distributed system makes these systems highly heterogeneous. System heterogeneity complicates the design of static applications tha...
We present a new systematic method of structuring information using mental models. This method can be used both to evaluate the efficiency of an information structure and to build...
Ishantha Lokuge, Stephen A. Gilbert, Whitman Richa...
Transfer learning concerns applying knowledge learned in one task (the source) to improve learning another related task (the target). In this paper, we use structure mapping, a ps...