- Award ID(s):
- 1915967
- NSF-PAR ID:
- 10344980
- Editor(s):
- Meila, Marina and
- Date Published:
- Journal Name:
- Proceedings of the 38th International Conference on Machine Learning
- Volume:
- 139
- Issue:
- 2021
- Page Range / eLocation ID:
- 10162--10172
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Random subsetting was not always optimal; subsetting matters and depends on data characteristics.
Sparse models from genomics performed better in 75% of cases than a standard method.
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