We present a novel hierarchical prior structure for supervised transfer learning in named entity recognition, motivated by the common structure of feature spaces for this task acr...
Currently, a large amount of data can be best represented as graphs, e.g., social networks, protein interaction networks, etc. The analysis of these networks is an urgent research ...
We study the retrieval task that ranks a set of objects for a given query in the pairwise preference learning framework. Recently researchers found out that raw features (e.g. word...
Xi Chen, Bing Bai, Yanjun Qi, Qihang Lin, Jaime G....
Most memory test algorithms are optimized tests for a particular memory technology and a particular set of fault models, under the assumption that the memory is bit-oriented; i.e....
We propose a hybrid generative/discriminative framework for semantic parsing which combines the hidden vector state (HVS) model and the hidden Markov support vector machines (HMSV...