Reinforcement learning problems are commonly tackled with temporal difference methods, which attempt to estimate the agent's optimal value function. In most real-world proble...
In this paper, we define the notion of approximate bisimulation relation between two continuous systems. While exact bisimulation requires that the observations of two systems ar...
We design a linear time approximation scheme for the GaleBerlekamp Switching Game and generalize it to a wider class of dense fragile minimization problems including the Nearest C...
Abstract. We present the first (to our knowledge) approximation algorithm for tensor clustering—a powerful generalization to basic 1D clustering. Tensors are increasingly common...
This paper investigates, for the first time in the literature, the approximation of min-max (regret) versions of classical problems like shortest path, minimum spanning tree, and ...
Hassene Aissi, Cristina Bazgan, Daniel Vanderpoote...