no code implementations • ICML 2020 • Xinjie Fan, Yuguang Yue, Purnamrita Sarkar, Y. X. Rachel Wang
Tuning hyperparameters for unsupervised learning problems is difficult in general due to the lack of ground truth for validation.
1 code implementation • 10 Sep 2023 • Matteo Sesia, Y. X. Rachel Wang, Xin Tong
This paper develops novel conformal prediction methods for classification tasks that can automatically adapt to random label contamination in the calibration sample, leading to more informative prediction sets with stronger coverage guarantees compared to state-of-the-art approaches.
no code implementations • 1 Oct 2022 • Lijia Wang, Y. X. Rachel Wang, Jingyi Jessica Li, Xin Tong
Here, we propose a hierarchical NP (H-NP) framework and an umbrella algorithm that generally adapts to popular classification methods and controls the under-classification errors with high probability.
no code implementations • 17 Oct 2019 • Xinjie Fan, Yuguang Yue, Purnamrita Sarkar, Y. X. Rachel Wang
In this paper, we provide a framework with provable guarantees for selecting hyperparameters in a number of distinct models.
no code implementations • 8 Aug 2019 • Tung-Yu Wu, Y. X. Rachel Wang, Wing H. Wong
To further extend the utility of the algorithm to high dimensional settings, we construct a proposal with forward and reverse moves using stochastic gradient and show that the construction leads to reasonable acceptance probabilities.
no code implementations • NeurIPS 2018 • Soumendu Sundar Mukherjee, Purnamrita Sarkar, Y. X. Rachel Wang, Bowei Yan
Variational approximation has been widely used in large-scale Bayesian inference recently, the simplest kind of which involves imposing a mean field assumption to approximate complicated latent structures.
2 code implementations • 30 Jul 2017 • Y. X. Rachel Wang, Purnamrita Sarkar, Oana Ursu, Anshul Kundaje, Peter J. Bickel
However, one of the drawbacks of community detection is that most methods take exchangeability of the nodes in the network for granted; whereas the nodes in this case, i. e. the positions on the chromosomes, are not exchangeable.
Applications Genomics