P2L: Predicting Transfer Learning for Images and Semantic Relations

By Bishwaranjan Bhattacharjee, John R. Render, Matthew Q. Hill, Parijat Dube, Siyu Huo, Michael R. Glass, Brian M. Belgodere, Noel C. F. Codella, Patrick Watson. 2019

Subfields: Computer Vision and Pattern Recognition, Representation & Self-Supervised Learning

How researchers see this paper

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

In Computer Vision and Pattern Recognition

1. Hayden S. Helm
2. Ronak D. Mehta
3. Carey E. Priebe
4. Joshua T. Vogelstein
5. Ali Geisa
6. Christopher M. White
7. Weiwei Yang
8. Brandon Duderstadt

In Representation & Self-Supervised Learning

1. Hayden S. Helm
2. Brandon Duderstadt
3. Ronak D. Mehta
4. Carey E. Priebe
5. Joshua T. Vogelstein
6. Ali Geisa
7. Christopher M. White
8. Weiwei Yang

Citations in the corpus

• A partition-based similarity for classification distributions (2020, background): “4 RELATED WORK There has been a flurry of recent empirical work (Kifer et al., 2004; Achille et al., 2019; Bao et al., 2018; Tran et al., 2019; Bhattacharjee et al., 2020; Nguyen et al., 2020) defining statistics that help to determine whether or not a particular model or representation learned on a”