Conference paper
A character-centric neural model for automated story generation
Danyang Liu, Juntao Li, et al.
AAAI 2020
In tracking of time-varying low-rank models of time-varying matrices, we present a method robust to both uniformlydistributed measurement noise and arbitrarily-distributed "sparse"noise. In theory, we bound the tracking error. In practice, our use of randomised coordinate descent is scalable and allows for encouraging results on changedetection.net, a benchmark.
Danyang Liu, Juntao Li, et al.
AAAI 2020
Raúl Fernández Díaz, Lam Thanh Hoang, et al.
IRB-AI-DD 2025
Federico Zipoli, Carlo Baldassari, et al.
npj Computational Materials
Mengyang Gu, Debarun Bhattacharjya, et al.
AAAI 2020