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Fast Design Space Exploration of Nonlinear Systems: Part II
In the second step, we use an inverse design to search over a continuous space and fine-tune the component values with the goal of improving the value of the objective function.
DISPATCH: Design Space Exploration of Cyber-Physical Systems
In the second step, we use an inverse design to search over a continuous space to fine-tune the component values and meet the diverse set of system requirements.
Policy Optimization for Linear-Quadratic Zero-Sum Mean-Field Type Games
In particular, the case in which the transition and utility functions depend on the state, the action of the controllers, and the mean of the state and the actions, is investigated.
Linear-Quadratic Zero-Sum Mean-Field Type Games: Optimality Conditions and Policy Optimization
In particular, the case in which the transition and utility functions depend on the state, the action of the controllers, and the mean of the state and the actions, is investigated.
CovidDeep: SARS-CoV-2/COVID-19 Test Based on Wearable Medical Sensors and Efficient Neural Networks
The novel coronavirus (SARS-CoV-2) has led to a pandemic.
Learning-based Resource Optimization in Ultra Reliable Low Latency HetNets
Modeling the latency and reliability constraints of users with probabilistic guarantees, the joint problem of user offloading and resource allocation (JUR) in a URLLC setting is formulated as an optimization problem to minimize the cost of serving users for the MBS.
