12 citations · 24 across the 4 of their papers we have counts for
4 papers
PC Layer: Polynomial Weight Preconditioning for Improving LLM Pre-Training
Senmiao Wang, Tiantian Fang, Haoran Zhang +4
We propose a preconditioning (PC) layer, a weight parameterization via polynomial preconditioner that ensures stable weight conditioning throughout LLM training. The PC module resh…
DigGAN: Discriminator gradIent Gap Regularization for GAN Training with Limited Data
Tiantian Fang, Ruoyu Sun, Alex Schwing
Generative adversarial nets (GANs) have been remarkably successful at learning to sample from distributions specified by a given dataset, particularly if the given dataset is reaso…
Towards a Better Global Loss Landscape of GANs
Ruoyu Sun, Tiantian Fang, Alex Schwing
Understanding of GAN training is still very limited. One major challenge is its non-convex-non-concave min-max objective, which may lead to sub-optimal local minima. In this work,…
Co-Generation with GANs using AIS based HMC
Tiantian Fang, Alexander G. Schwing
Inferring the most likely configuration for a subset of variables of a joint distribution given the remaining ones - which we refer to as co-generation - is an important challenge…