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Learning adaptive planning representations with natural language guidance
Effective planning in the real world requires not only world knowledge, but the ability to leverage that knowledge to build the right representation of the task at hand.
Characterizing the Implicit Bias of Regularized SGD in Rank Minimization
We study the bias of Stochastic Gradient Descent (SGD) to learn low-rank weight matrices when training deep neural networks.
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