Johns Hopkins University | Department of Computer Science
Vladimir Braverman is an Assistant Professor in the Department of Computer Science in the Whiting School of Engineering at the Johns Hopkins University. He received his PhD from UCLA in 2011. His main research interests include streaming and sketching algorithms, in particular, universal sketches for norms and functions. His research has been supported by DARPA, NSF, Google, Cisco and Nvidia.
Streaming and sketching algorithms have found applications in machine learning, astronomy, medicine, networking, natural language processing and other disciplines. The practicality of streaming and sketching algorithms stems from (1) simplicity and generality of the streaming model and (2) the ability to provide results in real time (e.g., in network monitoring) and represent Big Data with small “sketches” (e.g., in astronomy, statistics). In this talk we will give a gentle introduction to streaming and sketching algorithms and demonstrate their applicability in cosmological N-body simulations, network monitoring, and statistical inference on massive graphs. No prior knowledge of streaming or sketching algorithms is required.
This event will be webcast live, and archived, at http://netcast.cs.fiu.edu.