Archives for generalisation in deep learning
Recently, Yoshua Bengio and researchers from the University of Montreal, the Max-Planck Institute for Intelligent Systems and Google Research demonstrated how causal representation learning contributes to the robustness and generalisation of machine learning models. The team reviewed the fundamental concepts of causal inference and related them to crucial open problems of machine learning, including transfer…
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A team at NYU and Modl.ai have posited in their recent work, that simple image processing techniques (listed below) can improve the generalisation in deep reinforcement learning systems. RL systems are typically trained on gaming platforms which are test beds for teaching agents new tasks through visual cues. By exploiting the field of views of…
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