Society has reached a point of no return, one that leaves us completely reliant on omnipresent ICT-mediated communication. Mobile and sensor-rich portable devices connect millions of humans with Petabytes of data and numerous on-line services. However, tearing down the physical-digital barrier in a scalable fashion requires both radically novel algorithmic knowledge and in-depth understanding of humans and societies. We will deliver major theoretical advances in real-time intelligent information management of large datasets including online social networks, mobile devices and humans in physical space by delivering three functions: “alert”, by real-time location-aware knowledge acquisition, analysis and visualization; “response”, through on-demand composition and coordination of large teams; and effective “communication”, through recommendation and personalization.
Publication date
2019
SENSORS, 19 (16). ISSN 1424-8220
Session Recommendation via Recurrent Neural Networks over Fisher Embedding Vectors
In: 35th International Symposium on Computational Geometry, SoCG 2019 Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing, Dagstuhl, pp. 27:1-27:16.
Almost tight lower bounds for hard cutting problems in embedded graphs
In: 29th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2018 Society for Industrial and Applied Mathematics (SIAM), Philadelphia (PA), pp. 2357-2376.
Algorithms based on ∗-algebras, and their applications to isomorphism of polynomials with one secret, group isomorphism, and polynomial identity testing