1 code implementation • 29 Apr 2023 • Zachary Izzo, Ruishan Liu, James Zou
To do this, simple parametric models are frequently used (e. g. coefficients of linear regression) but usually fitted on the whole dataset.
no code implementations • ICLR 2020 • Ruishan Liu, Akshay Balsubramani, James Zou
Optimal transport (OT) is a principled approach to align datasets, but a key challenge in applying OT is that we need to specify a transport cost function that accurately captures how the two datasets are related.
no code implementations • ICLR 2019 • Ruishan Liu, Nicolo Fusi, Lester Mackey
Our GAN-assisted model compression (GAN-MC) significantly improves student accuracy for expensive models such as deep neural networks and large random forests on both image and tabular datasets.
1 code implementation • ICLR 2019 • Ruishan Liu, Nicolo Fusi, Lester Mackey
Our GAN-assisted TSC (GAN-TSC) significantly improves student accuracy for expensive models such as large random forests and deep neural networks on both tabular and image datasets.
1 code implementation • 18 Oct 2017 • Ruishan Liu, James Zou
We show that even in this very simple setting, the amount of memory kept can substantially affect the agent's performance.