Divide and conquer algorithms are a good match for modern parallel machines: they tend to have large amounts of inherent parallelism and they work well with caches and deep memory...
This paper concerns learning and prediction with probabilistic models where the domain sizes of latent variables have no a priori upper-bound. Current approaches represent prior d...
For data-collection applications in sensor networks, it is important to ensure all data sources have equal (or weighted) access to network bandwidth so that the base stations rece...
— This paper presents an algorithm for distributed power control and scheduling over wireless ad hoc-networks, where the data rate on each link depends on the transmission power ...
Probabilistic latent semantic indexing (PLSI) represents documents of a collection as mixture proportions of latent topics, which are learned from the collection by an expectation...
Alexander Hinneburg, Hans-Henning Gabriel, Andr&eg...