1 citations · 1 across the 3 of their papers we have counts for
3 papers
stat.ME2023
Sharp-SSL: Selective high-dimensional axis-aligned random projections for semi-supervised learning
Tengyao Wang, Edgar Dobriban, Milana Gataric +1
We propose a new method for high-dimensional semi-supervised learning problems based on the careful aggregation of the results of a low-dimensional procedure applied to many axis-a…
stat.ML2023
Demystifying Disagreement-on-the-Line in High Dimensions
Donghwan Lee, Behrad Moniri, Xinmeng Huang +2
Evaluating the performance of machine learning models under distribution shift is challenging, especially when we only have unlabeled data from the shifted (target) domain, along w…
cs.LG2022★ 1 cited
PAC Prediction Sets for Meta-Learning
Sangdon Park, Edgar Dobriban, Insup Lee +1
Uncertainty quantification is a key component of machine learning models targeted at safety-critical systems such as in healthcare or autonomous vehicles. We study this problem in…