We show how a technique from signal processing known as zero-delay convolution can be used to develop more efficient dynamic programming algorithms for a broad class of stochastic...
We describe a new method for pruning in dynamic models based on running an adaptive filtering algorithm online during decoding to predict aspects of the scores in the near future....
Recognition using only visual evidence cannot always be successful due to limitations of information and resources available during training. Considering relation among lexicon en...
In this paper, we establish a theoretical framework for a new concept of scheduling called soft scheduling. In contrasts to the traditional schedulers referred as hard schedulers,...
To model combinatorial decision problems involving uncertainty and probability, we introduce stochastic constraint programming. Stochastic constraint programs contain both decision...