Recent advancements in model-based reinforcement learning have shown that the dynamics of many structured domains (e.g. DBNs) can be learned with tractable sample complexity, desp...
Thomas J. Walsh, Sergiu Goschin, Michael L. Littma...
Low-Complexity Regions (LCRs) of biological sequences are the main source of false positives in similarity searches for biological sequence databases. We consider the problem of ï...
The development of technologies to address machine translation and distillation of multilingual broadcast data depends heavily on the collection of large volumes of material from ...
Many applications involve a set of prediction tasks that must be accomplished sequentially through user interaction. If the tasks are interdependent, the order in which they are p...
We present a general machine learning framework for modelling the phenomenon of missing information in data. We propose a masking process model to capture the stochastic nature of...