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Found 3 papers, 1 papers with code
Learning What and Where to Transfer
To address the issue, we propose a novel transfer learning approach based on meta-learning that can automatically learn what knowledge to transfer from the source network to where in the target network.
Rapid Mixing Swendsen-Wang Sampler for Stochastic Partitioned Attractive Models
The Gibbs sampler is a particularly popular Markov chain used for learning and inference problems in Graphical Models (GMs).
Iterative Bayesian Learning for Crowdsourced Regression
Crowdsourcing platforms emerged as popular venues for purchasing human intelligence at low cost for large volume of tasks.
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