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stat.ML2013★ 3 cited
Scalable Probabilistic Entity-Topic Modeling
Neil Houlsby, Massimiliano Ciaramita
We present an LDA approach to entity disambiguation. Each topic is associated with a Wikipedia article and topics generate either content words or entity mentions. Training such mo…
stat.ML2011★ 475 cited
Bayesian Active Learning for Classification and Preference Learning
Neil Houlsby, Ferenc Huszár, Zoubin Ghahramani +1
Information theoretic active learning has been widely studied for probabilistic models. For simple regression an optimal myopic policy is easily tractable. However, for other tasks…