Statistical Learning and Data Science

Open access

ISSN: 3051-3901

Statistical Learning and Data Science

Open access

Advisory Board Members

David Donoho
Jianqing Fan
Michael I. Jordan
Jun Liu
Wing Hung Wong

Editorial Board

Statistical Learning and Data Science (SLADS) is a peer-reviewed quarterly journal sponsored by the Chinese Academy of Sciences, serving the international statistics community. The journal publishes c...

Statistical Learning and Data Science (SLADS) is a peer-reviewed quarterly journal sponsored by the Chinese Academy of Sciences, serving the international statistics community. The journal publishes cutting-edge research while fostering discussions about future developments across all data-driven disciplines, including economics, social sciences, biology, physics, engineering, health sciences, and humanities. Dedicated to publishing only the highest quality, field-impacting research in the area of statistics, machine learning, and data science, SLADS features

Open:         

Full open access with waived article processing charges (APCs)

Transparent open peer review process while maintaining rigorous standards

Fast:          

Desk rejection within 7 days

First post-review decision within 60 days of submission

Immediate online publication of accepted manuscripts (pre-copyedited version)

Online publication (copyedited and proofed) within 7 days of final acceptance

Diverse:     

Regular sections include: Research papers, Review papers, Discussion papers, Perspectives, and Special topics.

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