Batch active learning is reformulated as sparse subset approximation of the expected complete-data log-posterior, solved with Frank-Wolfe and random projections.
Active learning
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.ML 1years
2019 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Bayesian Batch Active Learning as Sparse Subset Approximation
Batch active learning is reformulated as sparse subset approximation of the expected complete-data log-posterior, solved with Frank-Wolfe and random projections.