External Links

Cite Key

Statistics

  • References: 0
  • Cited by: 0
  • Reviews: 0
  • Bibliographies: 0

PDF

Researchr

Researchr is a web site for finding, collecting, sharing, and reviewing scientific publications, for researchers by researchers.

Sign up for an account to create a profile with publication list, tag and review your related work, and share bibliographies with your co-authors.

Tackling Instance-Dependent Label Noise via a Universal Probabilistic Model

Qizhou Wang, Bo Han 0003, Tongliang Liu, Gang Niu 0001, Jian Yang, Chen Gong 0002. Tackling Instance-Dependent Label Noise via a Universal Probabilistic Model. In Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Thirty-Third Conference on Innovative Applications of Artificial Intelligence, IAAI 2021, The Eleventh Symposium on Educational Advances in Artificial Intelligence, EAAI 2021, Virtual Event, February 2-9, 2021. pages 10183-10191, AAAI Press, 2021. [doi]

Authors

Qizhou Wang

This author has not been identified. Look up 'Qizhou Wang' in Google

Bo Han 0003

This author has not been identified. Look up 'Bo Han 0003' in Google

Tongliang Liu

This author has not been identified. Look up 'Tongliang Liu' in Google

Gang Niu 0001

This author has not been identified. Look up 'Gang Niu 0001' in Google

Jian Yang

This author has not been identified. Look up 'Jian Yang' in Google

Chen Gong 0002

This author has not been identified. Look up 'Chen Gong 0002' in Google
runs on