Berkeley’s Professor David E. Culler discusses the future of data science, the “Berkeley view” of the field, and the biggest challenges for data scientists today.
The ABRA suite of algorithms computes and maintains high-quality approximations of the betweenness centrality of all nodes or edges on static and fully dynamic graphs.
TRIÈST is a suite of sampling-based, one-pass algorithms for approximate triangle counting from fully-dynamic edge streams.
Comparing big graph centrality measures, approximation algorithm quality guarantees, and the trade-offs and scalability behaviors of distributed algorithms.
Higher-order Attribute Contraction Schemes (HACS), a language for programming compilers, makes it possible to create a full compiler from a single source file.