Proposing Determined Multi-Label Learning to reduce labeling costs in multi-label tasks.
Deep Dependency Networks (DDNs) combined with advanced inference schemes, such as local search and integer linear programming, outperform basic neural networks and hybrid models of neural networks and Markov random fields in multi-label classification tasks.