863 citations · 1.1k across the 19 of their papers we have counts for
4 papers · 1 filter
Machine Learning with a Reject Option: A survey
Kilian Hendrickx, Lorenzo Perini, Dries Van der Plas +2
Machine learning models always make a prediction, even when it is likely to be inaccurate. This behavior should be avoided in many decision support applications, where mistakes can…
GRAPHOPT: constrained-optimization-based parallelization of irregular graphs
Nimish Shah, Wannes Meert, Marian Verhelst
Sparse, irregular graphs show up in various applications like linear algebra, machine learning, engineering simulations, robotic control, etc. These graphs have a high degree of pa…
Acceleration of probabilistic reasoning through custom processor architecture
Nimish Shah, Laura I. Galindez Olascoaga, Wannes Meert +1
Probabilistic reasoning is an essential tool for robust decision-making systems because of its ability to explicitly handle real-world uncertainty, constraints and causal relations…
ProbLP: A framework for low-precision probabilistic inference
Nimish Shah, Laura I. Galindez Olascoaga, Wannes Meert +1
Bayesian reasoning is a powerful mechanism for probabilistic inference in smart edge-devices. During such inferences, a low-precision arithmetic representation can enable improved…