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cs.LG2021★ 2 cited
Being Properly Improper
Tyler Sypherd, Richard Nock, Lalitha Sankar
Properness for supervised losses stipulates that the loss function shapes the learning algorithm towards the true posterior of the data generating distribution. Unfortunately, data…
cs.LG2021
Realizing GANs via a Tunable Loss Function
Gowtham R. Kurri, Tyler Sypherd, Lalitha Sankar
We introduce a tunable GAN, called -GAN, parameterized by , which interpolates between various -GANs and Integral Probability Metric based GANs (under constr…