J. Schultz

Computer Vision and Pattern Recognition · with Crawford · 2013–2021

A researcher in the Science corpus: 3 papers; trusts 1 researcher and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 20 citations into it

Whom J. Schultz trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Alex Krizhevsky

Who trusts J. Schultz overall

1. Jacob Metcalf
2. Kate Crawford
3. Madalina Busuioc

Papers from J. Schultz's perspective

Ordered by how strongly the researchers J. Schultz trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet: A large-scale hierarchical image database
2. Learning Multiple Layers of Features from Tiny Images
3. Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer (Journal of machine learning research)
4. Model Cards for Model Reporting
5. Datasheets for datasets
6. Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification
7. Extracting Training Data from Large Language Models
8. Data and its (dis)contents: A survey of dataset development and use in machine learning research
9. Sorting Things Out: Classification and Its Consequences
10. No Classification without Representation: Assessing Geodiversity Issues in Open Data Sets for the Developing World

Their papers

• A Framework for Deprecating Datasets: Standardizing Documentation, Identification, and Communication (2021) — 39 citations
• Dirty Data, Bad Predictions: How Civil Rights Violations Impact Police Data, Predictive Policing Systems, and Justice (2019)
• Big Data and Due Process: Toward a Framework to Redress Predictive Privacy Harms (2013) — 470 citations