We propose a new machine learning paradigm called Graph Transformer Networks that extends the applicability of gradient-based learning algorithms to systems composed of modules th...
Structured output prediction is an important machine learning problem both in theory and practice, and the max-margin Markov network (M3 N) is an effective approach. All state-of-...
Node pruning is a commonly used technique for solution acceleration in a dynamic programming network. In pruning, nodes are adaptively removed from the dynamic programming network...
Matthew D. Bailey, Robert L. Smith, Jeffrey M. Ald...
Parallel text alignment is a special type of pattern recognition task aimed to discover the similarity between two sequences of symbols. Given the same text in two different langua...
The resource-constrained elementary shortest path problem arises as a pricing subproblem in branch-and-price algorithms for vehicle routing problems with additional constraints. W...