T-LoHo: A Bayesian Regularization Model for Structured Sparsity and Smoothness on Graphs

Changwoo J. Lee, Zhao Tang Luo, Huiyan Sang. T-LoHo: A Bayesian Regularization Model for Structured Sparsity and Smoothness on Graphs. In Marc'Aurelio Ranzato, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, Jennifer Wortman Vaughan, editors, Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual. pages 598-609, 2021. [doi]

@inproceedings{LeeLS21-5,
  title = {T-LoHo: A Bayesian Regularization Model for Structured Sparsity and Smoothness on Graphs},
  author = {Changwoo J. Lee and Zhao Tang Luo and Huiyan Sang},
  year = {2021},
  url = {https://proceedings.neurips.cc/paper/2021/hash/05a70454516ecd9194c293b0e415777f-Abstract.html},
  researchr = {https://researchr.org/publication/LeeLS21-5},
  cites = {0},
  citedby = {0},
  pages = {598-609},
  booktitle = {Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual},
  editor = {Marc'Aurelio Ranzato and Alina Beygelzimer and Yann N. Dauphin and Percy Liang and Jennifer Wortman Vaughan},
}