Unlike unsupervised approaches such as autoencoders that learn to reconstruct their inputs, this paper introduces an alternative approach to unsupervised feature learning called d...
Paul A. Szerlip, Gregory Morse, Justin K. Pugh, Ke...
Heuristic search is a state-of-the-art approach to classical planning. Several heuristic families were developed over the years to automatically estimate goal distance information...
Alexander Shleyfman, Michael Katz 0001, Malte Helm...
Human computation or crowdsourcing involves joint inference of the ground-truth-answers and the workerabilities by optimizing an objective function, for instance, by maximizing th...
In many learning tasks with structural properties, structural sparsity methods help induce sparse models, usually leading to better interpretability and higher generalization perf...
PDDL+ planning involves reasoning about mixed discretecontinuous change over time. Nearly all PDDL+ planners assume that continuous change is linear. We present a new technique th...
Daniel Bryce, Sicun Gao, David J. Musliner, Robert...