Stochastic satisfiability modulo theories (SSMT), which is an extension of satisfiability modulo theories with randomized quantification, has successfully been used as a symboli...
In the realm of multilabel classification (MLC), it has become an opinio communis that optimal predictive performance can only be achieved by learners that explicitly take label d...
We introduce a novel approach for robust belief tracking of user intention within a spoken dialog system. The space of user intentions is modeled by a probabilistic extension of t...
Neville Mehta, Rakesh Gupta, Antoine Raux, Deepak ...
: Indefinite probabilities are a novel technique for quantifying uncertainty, which were created as part of the PLN (Probabilistic Logic Networks) logical inference engine, which i...
Hardware predictor designers have incorporated hysteresis and/or bias to achieve desired behavior by increasing the number of bits per counter. Some resulting proposed predictor de...