Problems that can be sampled randomly are a good source of test suites for comparing quality of constraint satisfaction techniques. Quasigroup problems are representatives of struc...
We show that for any constant ε > 0, there is no Ω(log1−ε M)approximation algorithm for the directed congestion minimization problem on networks of size M unless NP ⊆ Z...
The Steiner tree problem in weighted graphs seeks a minimum weight connected subgraph containing a given subset of the vertices terminals. We present a new polynomial-time heurist...
The low-rank matrix approximation problem involves finding of a rank k version of a m ? n matrix AAA, labeled AAAk, such that AAAk is as "close" as possible to the best ...
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...