We propose a novel framework for imposing label ordering constraints in multilabel optimization. In particular, label jumps can be penalized differently depending on the jump dire...
Effective access to knowledge within large declarative memory stores is one challenge in the development and understanding of long-living, generally intelligent agents. We focus o...
A common approach in machine learning is to use a large amount of labeled data to train a model. Usually this model can then only be used to classify data in the same feature spac...
Abstract. The prediction of diagnosis codes is typically based on freetext entries in clinical documents. Previous attempts to tackle this problem range from strictly rule-based sy...
Recent work in communications and business modeling emphasizes a commitment-based view of interaction. By abstracting away from implementation-level details, commitments can poten...