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Size-Noise Tradeoffs in Generative Networks
Bolton Bailey, Matus J. Telgarsky
Neural Information Processing Systems http://nips.cc/
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Predicting Ground State Properties: Constant Sample Complexity and Deep Learning Algorithms
Our first algorithm consists of a simple modification of the ML model used by Lewis et al. and applies to a property of interest known in advance.
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LogarithmicRegretBoundinPartiallyObservable LinearDynamicalSystems
Over time,ADAPTON improves its model estimates and obtains more accurate gradient updates to improve the controller.
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TheMechanismofPrediction HeadinNon-contrastive Self-supervisedLearning
The substitution effect happens when learning the stronger features insome neurons can substitute for learning these features in other neurons through updating the predictionhead.
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