Scaling up real networks by geometric branching growth

Hidden geometric correlations in real multiplex networks

Real networks often form interacting parts of larger and more complex systems. Examples can be found in di erent domains, ranging from the Internet to structural and functional brain networks. Here, we show that these multiplex systems are not random combinations of single network layers. Instead, they are organized in specific ways dictated by hidden geometric correlations between the layers. ...

Geometric microphone array calibration by multidimensional scaling

Classical multidimensional scaling is a simple, linear technique for finding coordinates of points given their interpoint distances. In this paper we describe the algorithm and show how it can be used to solve the geometric microphone array calibration problem. The method requires no complicated hardware or calibration targets, just a tape measure (or similar measuring device). We also extend t...

Scaling up Planning by teasing out

ION SWITCH Planning Done ? Resources Alloc ? NO YES NO YES NO YES PLANNER

Scaling Up Robust MDPs by Reinforcement Learning

We consider large-scale Markov decision processes (MDPs) with parameter uncertainty, under the robust MDP paradigm. Previous studies showed that robust MDPs, based on a minimax approach to handle uncertainty, can be solved using dynamic programming for small to medium sized problems. However, due to the “curse of dimensionality”, MDPs that model real-life problems are typically prohibitively la...

Scaling Up