We study the problem of strong/weak bisimilarity between processes of one-counter automata and finite-state processes. We show that the problem of weak bisimilarity between process...
We present black-box techniques for learning how to interleave the execution of multiple heuristics in order to improve average-case performance. In our model, a user is given a s...
Matthew J. Streeter, Daniel Golovin, Stephen F. Sm...
We study online learning when individual instances are corrupted by adversarially chosen random noise. We assume the noise distribution is unknown, and may change over time with n...
Much research in the area of constraint processing has recently been focused on extracting small unsatisfiable "cores" from unsatisfiable constraint systems with the goal...
Parallel programming has proven to be an effective technique to improve the performance of computationally intensive applications. However, writing parallel programs is not easy, ...
Roberto Di Cosmo, Zheng Li, Susanna Pelagatti, Pie...