We apply a new active learning formulation to the problem of learning medical concepts from unstructured text. The new formulation is based on maximizing the mutual information th...
We propose a new approach to reinforcement learning which combines least squares function approximation with policy iteration. Our method is model-free and completely off policy. ...
Generally, the task in a distributed system must achieve an agreement. It requires a set of processors to agree on a common value even if some components are corrupted. There are s...
This paper investigates topology management of large wireless sensor networks. Due to their random deployment, nodes have to organize themselves as energy efficient as possible to ...
Jakob Salzmann, Ralf Behnke, Jiaxi You, Dirk Timme...
This paper continues the investigation of the connection between probabilistically checkable proofs PCPs the approximability of NP-optimization problems. The emphasis is on prov...