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View all- Chuprov SReznik LGrigoryan G(2023)Study on Network Importance for ML End Application RobustnessICC 2023 - IEEE International Conference on Communications10.1109/ICC45041.2023.10279698(6627-6632)Online publication date: 28-May-2023
Responsible AI becomes critical where robustness and fairness must be satisfied together. Traditionally, the two topics have been studied by different communities for different applications. Robust training is designed for noisy or poisoned data where ...
Classical linear/shallow learning is relatively easy to analyze and understand, but the power of deep learning is often desirable. I am developing a hybrid approach in order to obtain learning algorithms that are both trustworthy and accurate. My ...
Under a multi rate network scenario, the IEEE 802.11 DCF MAC fails to provide air-time fairness for all competing stations since the protocol is designed for ensuring max-min throughput fairness and the maximum achievable throughput by any station gets ...
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