We study learning scenarios in which multiple learners are involved and “nature” imposes some constraints that force the predictions of these learners to behave coherently. Thi...
For many supervised learning tasks it is very costly to produce training data with class labels. Active learning acquires data incrementally, at each stage using the model learned...
Our world is increasingly data-driven. The growth and value of data continue to exceed all predictions. Potential for business opportunity, economic growth, scientific discovery, ...
Visual interpretation of events requires both an appropriate representation of change occurring in the scene and the application of semantics for differentiating between different...
Intelligent planning algorithms such as the Partially Observable Markov Decision Process (POMDP) have succeeded in dialog management applications [10, 11, 12] because of their rob...