Time-sensitive network experiments are difficult. There are major challenges involved in generating high volumes of sufficiently realistic traffic. Additionally, accurately measur...
Neda Beheshti, Yashar Ganjali, Monia Ghobadi, Nick...
Clustering constitutes an ubiquitous problem when dealing with huge data sets for data compression, visualization, or preprocessing. Prototype-based neural methods such as neural g...
Alexander Hasenfuss, Barbara Hammer, Fabrice Rossi
In the nanometer manufacturing region, process variation causes significant uncertainty for circuit performance verification. Statistical static timing analysis (SSTA) is thus dev...
Recent work in transfer learning has succeeded in making reinforcement learning algorithms more efficient by incorporating knowledge from previous tasks. However, such methods typ...
Many applications on blog search and mining often meet the challenge of handling huge volume of blog data, in which one single blog could contain hundreds or even thousands of ent...
Jinfeng Zhuang, Steven C. H. Hoi, Aixin Sun, Rong ...