Requirements engineers need to make sure that the requirements models and specifications they are building do accurately capture what stakeholders really want. Requirements animat...
Hung Tran Van, Axel van Lamsweerde, Philippe Masso...
We consider reinforcement learning in the parameterized setup, where the model is known to belong to a parameterized family of Markov Decision Processes (MDPs). We further impose ...
We study the problem of uncertainty in the entries of the Kernel matrix, arising in SVM formulation. Using Chance Constraint Programming and a novel large deviation inequality we ...
Researchers have made great strides in improving the fault tolerance of both centralized and replicated systems against arbitrary (Byzantine) faults. However, there are hard limit...
Byung-Gon Chun, Petros Maniatis, Scott Shenker, Jo...
This paper investigates a learning control using iterative error compensation for uncertain systems to enhance the precision of high speed, computer controlled machining process. ...