Statistical Learning
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Generalization Error Analysis of Quantized Compressive Learning
Neural Information Processing Systems
In this paper,we consider the learning problem where the projected data isfurther compressed byscalarquantization, which iscalled quantized compressivelearning. Generalization error bounds are derived for three models: nearest neighbor (NN) classifier, linear classifier and least squares regression.
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Zero-shot Learning via Simultaneous Generating and Learning
Neural Information Processing Systems
Neural Information Processing Systems http://nips.cc/
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Large Scale Adversarial Representation Learning
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Neural Information Processing Systems http://nips.cc/
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