Challenges in Data Crowdsourcing

By Hector Garcia-Molina, Manas R. Joglekar, Adam Marcus, Aditya G. Parameswaran, Vasilis Verroios. 2016

133 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Science Applications

How researchers see this paper

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

In Artificial Intelligence

1. Hangyu Zhu
2. Shiqing Liu
3. Jinjin Xu
4. Yaochu Jin
5. Yuji Roh
6. Steven Euijong Whang
7. Geon Heo
8. Handing Wang

In Computer Science Applications

1. Shiqing Liu
2. Jinjin Xu
3. Yaochu Jin
4. Hangyu Zhu
5. Geon Heo
6. Yuji Roh
7. Steven Euijong Whang

Citations in the corpus

• A Survey on Data Collection for Machine Learning: A Big Data - AI Integration Perspective (2018, background): “A recent survey [88] provides an extensive discussion”
• Federated Learning on Non-IID Data: A Survey (2021, background): “Crowdsourcing data [34] is a more complex situation where data labels can be noisy, posing serious challenges to information collection in many centralized machine learning tasks, let alone in FL tasks.”