no code implementations • ICML 2020 • Yuchao Cai, Hanyuan Hang, Hanfang Yang, Zhouchen Lin
In this paper, we propose a boosting algorithm for regression problems called \textit{boosted histogram transform for regression} (BHTR) based on histogram transforms composed of random rotations, stretchings, and translations.
no code implementations • 2 Dec 2023 • Yuchao Cai, Yuheng Ma, Hanfang Yang, Hanyuan Hang
We consider the paradigm of unsupervised anomaly detection, which involves the identification of anomalies within a dataset in the absence of labeled examples.
no code implementations • 1 Sep 2021 • Hanyuan Hang, Yuchao Cai, Hanfang Yang, Zhouchen Lin
In this paper, we propose an ensemble learning algorithm called \textit{under-bagging $k$-nearest neighbors} (\textit{under-bagging $k$-NN}) for imbalanced classification problems.
no code implementations • 3 Jun 2021 • Hanyuan Hang, Tao Huang, Yuchao Cai, Hanfang Yang, Zhouchen Lin
In this paper, we propose a gradient boosting algorithm for large-scale regression problems called \textit{Gradient Boosted Binary Histogram Ensemble} (GBBHE) based on binary histogram partition and ensemble learning.
no code implementations • 24 Jun 2019 • Hanyuan Hang, Yuchao Cai, Hanfang Yang
Single-level density-based approach has long been widely acknowledged to be a conceptually and mathematically convincing clustering method.