Foundations of Safe Learning (2019 Workshop)
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Join us for the IBM Research Foundations of Safe Learning 2019 workshop scheduled during the IBM AI Research Week in Cambridge, Massachusetts!
As deep learning moves from the lab into real-world applications, ensuring the correctness and robustness of deep neural networks becomes a paramount concern. Specifying what it means for a neural network to behave correctly is a challenging problem, especially for classifiers and generative models. Verifying that deep networks meet these specifications is computationally challenging.
Recent demonstrations of brittleness in deep learning – including adversarial examples and RL agents that learn pathological control policies – have motivated new computationally tractable approaches toward both specifying and verifying salient properties of neural networks. This workshop will bring together academics, industry researchers, and practitioners to delve into the current state of safe learning. Relevant topics include robustness evaluation/verification, safe reinforcement learning, fairness, robustness against model compression, interpretability, and deep learning with invariance and equivariance constraints.
To Register, please click on the Register button (above).
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