Progress & Compress: A scalable framework for continual learning

ICML 2018 Jonathan SchwarzJelena LuketinaWojciech M. CzarneckiAgnieszka Grabska-BarwinskaYee Whye TehRazvan PascanuRaia Hadsell

We introduce a conceptually simple and scalable framework for continual learning domains where tasks are learned sequentially. Our method is constant in the number of parameters and is designed to preserve performance on previously encountered tasks while accelerating learning progress on subsequent problems... (read more)

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