Randomized algorithms have been recently receiving immense research attention due to their rich diversity and wide applicability. In the talk, we present challenges of big data analytics in algorithmic aspects and highlight the important role of randomization in algorithm design for a wide range of data-intensive applications.

In particular, the presentation will illustrate how to exploit randomization for speeding up basic problems in computer science, including  similarity search in information retrieval, and training kernel machines in machine learning. The presentation concludes with future research directions on this line of research.