Leakage power reduction in cache memories continues to be a critical area of research because of the promise of a significant pay-off. Various techniques have been developed so fa...
Recent multi-agent extensions of Q-Learning require knowledge of other agents’ payoffs and Q-functions, and assume game-theoretic play at all times by all other agents. This pap...
This paper investigates the effects of demand risk on the performance of supply chain in continuous time setting. The inventory level has been modeled as a jump-diffusion process ...
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...
In this paper, we address the matrix completion problem and propose a novel algorithm based on a smoothed rank function (SRF) approximation. Among available algorithms like FPCA a...