413 citations · 1.2k across the 20 of their papers we have counts for
4 papers · 1 filter
Data-driven Random Fourier Features using Stein Effect
Wei-Cheng Chang, Chun-Liang Li, Yiming Yang +1
Large-scale kernel approximation is an important problem in machine learning research. Approaches using random Fourier features have become increasingly popular [Rahimi and Recht,…
MMD GAN: Towards Deeper Understanding of Moment Matching Network
Chun-Liang Li, Wei-Cheng Chang, Yu Cheng +2
Generative moment matching network (GMMN) is a deep generative model that differs from Generative Adversarial Network (GAN) by replacing the discriminator in GAN with a two-sample…
One Network to Solve Them All --- Solving Linear Inverse Problems using Deep Projection Models
J. H. Rick Chang, Chun-Liang Li, Barnabas Poczos +2
While deep learning methods have achieved state-of-the-art performance in many challenging inverse problems like image inpainting and super-resolution, they invariably involve prob…
CMU DeepLens: Deep Learning For Automatic Image-based Galaxy-Galaxy Strong Lens Finding
Francois Lanusse, Quanbin Ma, Nan Li +5
Galaxy-scale strong gravitational lensing is not only a valuable probe of the dark matter distribution of massive galaxies, but can also provide valuable cosmological constraints,…