Multi-instance learning deals with problems that treat bags of instances as training examples. In single-instance learning problems, dimensionality reduction is an essential step ...
We present a data symmetry reduction approach for model temporal-epistemic logic. The technique abstracts the epistemic indistinguishably relation for the knowledge operators, and ...
Mika Cohen, Mads Dam, Alessio Lomuscio, Hongyang Q...
Learning to rank is becoming an increasingly popular research area in machine learning. The ranking problem aims to induce an ordering or preference relations among a set of insta...
Agents with partial observability need to share information to achieve decentralised coordination. However, in resource-constrained systems, indiscriminate communication can creat...
Partha Sarathi Dutta, Claudia V. Goldman, Nicholas...
State-of-the-art statistical parsing models applied to free word-order languages tend to underperform compared to, e.g., parsing English. Constituency-based models often fail to c...