We present an approach for merging message streams from producers distributed over a network, using a deterministic algorithm that is independent of any nondeterminism of the syst...
This paper presents our Recurrent Control Neural Network (RCNN), which is a model-based approach for a data-efficient modelling and control of reinforcement learning problems in di...
—We consider a widely applicable model of resource allocation where two sequences of events are coupled: on a continuous time axis (t), network dynamics evolve over time. On a di...
Alexandre Proutiere, Yung Yi, Tian Lan, Mung Chian...
A central issue in the design of modern communication networks is that of providing performance guarantees. This issue is particularly important if the networks support real-time t...
The enormous number of questions needed to acquire a full preference model when the size of the outcome space is large forces us to work with partial models that approximate the u...