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Showing 1 to 3 of 3 for “"security and privacy, machine learning"”.

  1. Multi-model-based defense against adversarial examples for neural networks

    … many real-world tasks such as image recognition and can achieve high effectiveness on these tasks. Despite being popularly used in many applications, neural network models have been found to be vulnerable to adversarial examples, i.e., carefully crafted examples aiming to mislead machine learning

    uiuc Repository record for Multi-model-based defense against adversarial examples for neural networks (opens in a new tab)

  2. Diagnosis based specialist identification in the hospital

    … critical judgments. They are useful for training and staffing and provide confidence to patients that their providers have the experience needed to address their problems. This work evaluates how machine learning classifiers can be trained on treatment histories to recognize medical specialties. …

    uiuc Repository record for Diagnosis based specialist identification in the hospital (opens in a new tab)

  3. Building Trustworthy Artificial Intelligence of Things Systems in Adversarial Environments

    … a great explosion of artificial intelligence and the Internet of Things technologies. They have revolutionized people's daily lives, improving convenience, efficiency, and connectivity in previously unimaginable ways. Among all broad topics related to AI and IoT, the Artificial Intelligence of …

    vt Repository record for Building Trustworthy Artificial Intelligence of Things Systems in Adversarial Environments (opens in a new tab)