Wallonia
GAVEL: Generating Games Via Evolution and Language Models Graham T odd New York University Tandon Brooklyn, New York, USA gdrtodd Alexander G. Padula ETH Zurich Zurich, Switzerland apadula
Automatically generating novel and interesting games is a complex task.
How a student becomes a teacher: learning and forgetting through Spectral methods
The above scheme proves particularly relevant when the student network is overparameterized (namely, when larger layer sizes are employed) as compared to the underlying teacher network. Under these operating conditions, it is tempting to speculate that the student ability to handle the given task could be eventually stored in a sub-portion of the whole network.
How a student becomes a teacher: learning and forgetting through Spectral methods
The above scheme proves particularly relevant when the student network is overparameterized (namely, when larger layer sizes are employed) as compared to the underlying teacher network. Under these operating conditions, it is tempting to speculate that the student ability to handle the given task could be eventually stored in a sub-portion of the whole network.
Learning Cut Generating Functions for Integer Programming
CGF can outperform the GMI cuts for certain distributions.
neurips_2021_main
Made: Maskedautoencoder fordistributionestimation. In Francis Bachand David Blei, editors,Proceedingsofthe 32nd International Conferenceon Machine Learning, volume 37 ofProceedingsof Machine Learning Research, pages 881-889, Lille, France, 07-09 Jul 2015.
