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The DARPA Lifelong Learning Machines (L2M) program seeks to yield advances in artificial intelligence (AI) systems so that they are capable of learning (and improving) continuously, leveraging data on one task to improve performance on another, and doing so in a computationally sustainable way.
Estimates of the regression coefficient based on kendall’s tau
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Meta-consolidation for continual learning, 2020
K J Joseph and Vineeth N Balasubramanian · 2020
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Adaptive group sparse regularization for continual learning
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Continual learning of a mixed sequence of similar and dissimilar tasks
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Lifelong policy gradient learning of factored policies for faster training without forgetting
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Continual deep learning by functional regularisation of memorable past, 2021
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Cora: Benchmarks, baselines, and metrics as a platform for continual reinforcement learning agents, 2021
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