155 citations · 313 across the 3 of their papers we have counts for
3 papers
WebRED: Effective Pretraining And Finetuning For Relation Extraction On The Web
Robert Ormandi, Mohammad Saleh, Erin Winter +1
Relation extraction is used to populate knowledge bases that are important to many applications. Prior datasets used to train relation extraction models either suffer from noisy la…
Large scale distributed neural network training through online distillation
Rohan Anil, Gabriel Pereyra, Alexandre Passos +3
Techniques such as ensembling and distillation promise model quality improvements when paired with almost any base model. However, due to increased test-time cost (for ensembles) a…
Gossip Learning with Linear Models on Fully Distributed Data
Róbert Ormándi, István Hegedüs, Márk Jelasity
Machine learning over fully distributed data poses an important problem in peer-to-peer (P2P) applications. In this model we have one data record at each network node, but without…