We study the computational and sample complexity of parameter and structure learning in graphical models. Our main result shows that the class of factor graphs with bounded degree...
This paperconsidersthe problem of representingcomplex systems that evolve stochastically over time. Dynamic Bayesian networks provide a compact representation for stochastic proce...
We introduce transformations from time series data to the domain of complex networks which allow us to characterise the dynamics underlying the time series in terms of topological ...
Abstract--Protein complexes are important for understanding principles of cellular organization and functions. With the availability of large amounts of high-throughput proteinprot...
Guimei Liu, Chern Han Yong, Limsoon Wong, Hon Nian...
Entity information management (EIM) is a nascent IR research area that investigates the information management process about entities instead of documents. It is motivated by the ...