Machine Learning and Data Mining
Editor:
- Ali Shojaie (ashojaie@uw.edu), University of Washington
- Jelena Bradic, University of California, San Diego
- Zaid Harchaoui, University of Washington
- Jian Kang, University of Michigan
- Mladen Kolar, University of Chicago
- Eric Laber, Duke University
- Yufeng Liu, University of North Carolina, Chapel Hill
- Po-Ling Loh, Columbia University
- George Michailidis, University of Florida
- Annie Qu, University of California, Irvine
- Aaditya Ramdas, Carnegie Mellon University
The NEJSDS Machine Learning and Data Mining Section aims to disseminate original methodological, theoretical and computational research on statistical approaches for machine learning and data mining. The section seeks articles in both foundations of machine learning and artificial intelligence as well as novel applications across diverse scientific disciplines. The section also welcomes review articles on cutting-edge topics.