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Learning to Screen
Alon Cohen, Avinatan Hassidim, Haim Kaplan, Yishay Mansour, Shay Moran
Neural Information Processing Systems
Neural Information Processing Systems http://nips.cc/
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Calibration by Distribution Matching: Trainable Kernel Calibration Metrics Charles Marx
Neural Information Processing Systems
These metrics admit differentiable sample estimates, making it easy to incorporate a calibration objective into empirical risk minimization.
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Entropy-basedadaptiveHamiltonianMonteCarlo
Neural Information Processing Systems
Hamiltonian Monte Carlo (HMC) is a popular Markov Chain Monte Carlo (MCMC) algorithm to sample from an unnormalized probability distribution.
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class distribution is shared across datasets. (b) Compared to supervised learning (SL), CLIP's performance (measured by accuracy) is less biased by data frequency, and the classifier is notably
Neural Information Processing Systems
Severe data imbalance naturally exists among web-scale vision-language datasets.
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