SEFA, a supervised latent-variable model with stochastic encoders and a gradient-based acquisition score, outperforms RL and mutual-information baselines on active feature acquisition benchmarks.
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Stochastic Encodings for Active Feature Acquisition
SEFA, a supervised latent-variable model with stochastic encoders and a gradient-based acquisition score, outperforms RL and mutual-information baselines on active feature acquisition benchmarks.