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Beyond MLE: Convex Learning for Text Generation
Neural Information Processing Systems
Maximum likelihood estimation (MLE) is a statistical method used to estimate the parameters of a probability distribution that best explain the observed data.
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ScalabledesignofError-CorrectingOutputCodes usingDiscreteOptimizationwithGraphColoring
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Error-correcting codes have found many applications in machine learning.
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MomentumAdversarialDistillation: HandlingLarge DistributionShiftsinData-FreeKnowledge Distillation
Neural Information Processing Systems
The main idea istouseagenerator to synthesize data for training the student.
SAMRS: Scaling-up Remote Sensing Segmentation Dataset with Segment Anything Model: Supplementary Material Di Wang
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In addition, only the foreground categories are considered.
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