Abstract Decision procedures underlie many program analysis problems. Traditional program analysis algorithms attempt to prove some property about a single, statically-defined prog...
We present an integrated framework for learning asymmetric boosted classifiers and online learning to address the problem of online learning asymmetric boosted classifiers, which ...
We give an algorithm for the on-line learning of permutations. The algorithm maintains its uncertainty about the target permutation as a doubly stochastic weight matrix, and makes...
The multi-period newsvendor problem describes the dilemma of a newspaper salesman--how many paper should he purchase each day to resell, when he doesn't know the demand? We d...
Protocols for distributed systems make often use of random transitions to achieve a common goal. A popular example are randomized leader election protocols. We introduce probabilis...