In sequential prediction tasks, one repeatedly tries to predict the next element in a sequence. A classical way to solve these problems is to fit an order-n Markov model to the da...
We describe a set of supervised machine learning experiments centering on the construction of statistical models of WH-questions. These models, which are built from shallow lingui...
Finite-time optimal control problems with quadratic performance index for linear systems with linear constraints can be transformed into Quadratic Programs (QPs). Model Predictive ...
Francesco Borrelli, Mato Baotic, Jaroslav Pekar, G...
Process variability has a detrimental impact on the performance of memories and other system components, which can lead to parametric yield loss at the system level due to timing ...
Antonis Papanikolaou, T. Grabner, Miguel Miranda, ...
In recent work we showed that models constructed from planner performance data over a large suite of benchmark problems are surprisingly accurate; 91-99% accuracy for success and ...
Mark Roberts, Adele E. Howe, Brandon Wilson, Marie...