626 citations · 974 across the 18 of their papers we have counts for
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cs.LG2018
Dropout Regularization in Hierarchical Mixture of Experts
Ozan İrsoy, Ethem Alpaydın
Dropout is a very effective method in preventing overfitting and has become the go-to regularizer for multi-layer neural networks in recent years. Hierarchical mixture of experts i…
cs.LG2018
Continuously Constructive Deep Neural Networks
Ozan İrsoy, Ethem Alpaydın
Traditionally, deep learning algorithms update the network weights whereas the network architecture is chosen manually, using a process of trial and error. In this work, we propose…
cs.CL2018★ 4 cited
Collective Entity Disambiguation with Structured Gradient Tree Boosting
Yi Yang, Ozan Irsoy, Kazi Shefaet Rahman
We present a gradient-tree-boosting-based structured learning model for jointly disambiguating named entities in a document. Gradient tree boosting is a widely used machine learnin…