Identifying and controlling bias is a key problem in empirical sciences. Causal diagram theory provides graphical criteria for deciding whether and how causal effects can be iden...
CNF-BCP is a well-known propositional reasoner that extends clausal Boolean Constraint Propagation (BCP) to non-clausal theories. Although BCP has efficient linear-time implementa...
We bound the future loss when predicting any (computably) stochastic sequence online. Solomonoff finitely bounded the total deviation of his universal predictor M from the true ...
Single-Class Classification (SCC) seeks to distinguish one class of data from the universal set of multiple classes. We present a new SCC algorithm that efficiently computes an ac...
We present a randomized subexponential time, polynomial space parameterized algorithm for the k-Weighted Feedback Arc Set in Tournaments (k-FAST) problem. We also show that our alg...