We present at a new approach to finding aesthetically pleasing page layouts. We do not aim to find an optimal layout, rather the aim is to find a layout which is not obviously wro...
Policy gradient (PG) reinforcement learning algorithms have strong (local) convergence guarantees, but their learning performance is typically limited by a large variance in the e...
Internet today, has transformed into a global information hub. The increase in its usage and magnitude have sparkled various research problems. Because of the diverse user populat...
Particle filters (PFs) are powerful samplingbased inference/learning algorithms for dynamic Bayesian networks (DBNs). They allow us to treat, in a principled way, any type of prob...
Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, ...
A key feature in population based optimization algorithms is the ability to explore a search space and make a decision based on multiple solutions. In this paper, an incremental le...