Stochastic gradient descent (SGD) uses approximate gradients estimated from subsets of the training data and updates the parameters in an online fashion. This learning framework i...
As information becomes available in increasing amounts to a wide spectrum of users, the need for a shift towards a more user-centered information access paradigm arises. We develo...
We addressed two issues concerning the practical aspects of optimally scheduling web advertising proposed by Langheinrich et al. [5], which scheduling maximizes the total number o...
Action-based dependency parsing, also known as deterministic dependency parsing, has often been regarded as a time efficient parsing algorithm while its parsing accuracy is a littl...
Recent researches have highlighted the importance of developing a network with distributed problem solving abilities thus enhancing reliability with equal share of network resourc...