It is difficult to apply machine learning to new domains because often we lack labeled problem instances. In this paper, we provide a solution to this problem that leverages domai...
We study a general online convex optimization problem. We have a convex set S and an unknown sequence of cost functions c1, c2, . . . , and in each period, we choose a feasible po...
Abraham Flaxman, Adam Tauman Kalai, H. Brendan McM...
GENET is a heuristic repair algorithm which demonstrates impressive e ciency in solving some large-scale and hard instances of constraint satisfaction problems (CSPs). In this pap...
Kenneth M. F. Choi, Jimmy Ho-Man Lee, Peter J. Stu...
We study the problem of minimizing the expected cost of binary searching for data where the access cost is not fixed and depends on the last accessed element, such as data stored i...
Gonzalo Navarro, Ricardo A. Baeza-Yates, Eduardo F...
It is known that interprocedural detection of copy constants and elimination of faint code in parallel programs are undecidable problems, if base statements are assumed to execute...