Semi-Supervised Sparse Gaussian Classification: Provable Benefits of Unlabeled Data

Eyar Azar, Boaz Nadler. Semi-Supervised Sparse Gaussian Classification: Provable Benefits of Unlabeled Data. In Amir Globersons, Lester Mackey, Danielle Belgrave, Angela Fan, Ulrich Paquet, Jakub M. Tomczak, Cheng Zhang 0005, editors, Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, NeurIPS 2024, Vancouver, BC, Canada, December 10 - 15, 2024. 2024. [doi]

@inproceedings{AzarN24,
  title = {Semi-Supervised Sparse Gaussian Classification: Provable Benefits of Unlabeled Data},
  author = {Eyar Azar and Boaz Nadler},
  year = {2024},
  url = {http://papers.nips.cc/paper_files/paper/2024/hash/23fb7cd2350c3125db48a551ae28f4bf-Abstract-Conference.html},
  researchr = {https://researchr.org/publication/AzarN24},
  cites = {0},
  citedby = {0},
  booktitle = {Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, NeurIPS 2024, Vancouver, BC, Canada, December 10 - 15, 2024},
  editor = {Amir Globersons and Lester Mackey and Danielle Belgrave and Angela Fan and Ulrich Paquet and Jakub M. Tomczak and Cheng Zhang 0005},
}