Interactive Machine Learning via a GPU-accelerated Toolkit

By Biye Jiang, John F. Canny. 2017

16 citations recorded by the source corpus.

Subfields: Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition, ML Systems & Hardware, Human-Computer Interaction

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Graphics and Computer-Aided Design

1. Antonio Torralba
2. David Bau
3. Jun-Yan Zhu
4. Tongzhou Wang
5. Richard Zhang
6. Eli Shechtman
7. Alexei A. Efros

In Computer Vision and Pattern Recognition

1. David Bau
2. Jun-Yan Zhu
3. Antonio Torralba
4. Luc Van Gool
5. Ming-Hsuan Yang
6. Andrea Vedaldi
7. Dacheng Tao
8. Trevor Darrell

In Human-Computer Interaction

1. Antonio Torralba
2. Ali Borji

Citations in the corpus

• Rewriting a Deep Generative Model (2020, background): “Interactive machine learning systems aim to improve training through human interaction in labeling [15,22,68], or by allowing a user to to aid in the model optimization process via interactive feature selection [19,27,64,50] or model and hyperparameter selection [39,61,37].”