Localization in wireless sensor networks (WSNs) is regarded as an emerging technology for
numerous cyber-physical system applications, which equips wireless sensors with the …

We describe distributed algorithms for two widely-used topic models, namely the Latent
Dirichlet Allocation (LDA) model, and the Hierarchical Dirichet Process (HDP) model. In our …

Gossip-based communication protocols are appealing in large-scale distributed applications
such as information dissemination, aggregation, and overlay topology management. This …

Unstructured overlays form an important class of peer-to-peer networks, notably when
content-based searching is at stake. The construction of these overlays, which is essentially …

We investigate the problem of learning a widely-used latent-variable model–the Latent
Dirichlet Allocation (LDA) or “topic” model–using distributed computation, where each of …

The Web abounds with dyadic data that keeps increasing by every single second. Previous
work has repeatedly shown the usefulness of extracting the interaction structure inside …

Machine learning over fully distributed data poses an important problem in peer‐to‐peer
applications. In this model, we have one data record at each network node but without the …

Clustering spatially distributed data is well motivated and especially challenging when
communication to a central processing unit is discouraged, eg, due to power constraints …

Automobile traffic is a major problem in developed societies. We collectively waste huge
amounts of time and resources traveling through traffic congestion. Drivers choose the route …

Distributed learning is a problem of fundamental interest in machine learning and cognitive
science. In this paper, we present asynchronous distributed learning algorithms for two well …