Upcoming Seminars

Abstract

Gaussian Boson sampling is a comparatively easy-to-engineer quantum computing approach. It has been considered notably to solve graph estimation problems such as detection of dense subgraphs. In this talk we report our findings on the limitations of Gaussian Boson sampling for achieving quantum advantage on the so-called planted biclique detection problem.

Speaker's Bio

Laurent Massoulié is a research scientist at Inria, scientific director of the Paris Inria Centre and professor at the Applied Maths Centre of Ecole Polytechnique. His research interests are in machine learning, probabilistic modelling and algorithms for networks. He has held research scientist positions at: France Telecom, Microsoft Research, Thomson-Technicolor, where he headed the Paris Research Lab. He obtained best paper awards at IEEE INFOCOM 1999, ACM SIGMETRICS 2005, ACM CoNEXT 2007, NeurIPS 2018, NeurIPS 2021, was elected "Technicolor Fellow" in 2011, received the  "Grand Prix Scientifique" of the Del Duca Foundation delivered by the French Academy of Science in 2017, is a Fellow of the "Prairie" Institute and received the ACM Sigmetrics achievement award in 2023.