7 citations · 32 across the 21 of their papers we have counts for
5 papers · 1 filter
Local Adaptivity of Gradient Boosting in Histogram Transform Ensemble Learning
Hanyuan Hang
In this paper, we propose a gradient boosting algorithm called \textit{adaptive boosting histogram transform} (\textit{ABHT}) for regression to illustrate the local adaptivity of g…
Under-bagging Nearest Neighbors for Imbalanced Classification
Hanyuan Hang, Yuchao Cai, Hanfang Yang +1
In this paper, we propose an ensemble learning algorithm called \textit{under-bagging -nearest neighbors} (\textit{under-bagging -NN}) for imbalanced classification problems.…
GBHT: Gradient Boosting Histogram Transform for Density Estimation
Jingyi Cui, Hanyuan Hang, Yisen Wang +1
In this paper, we propose a density estimation algorithm called \textit{Gradient Boosting Histogram Transform} (GBHT), where we adopt the \textit{Negative Log Likelihood} as the lo…
Leveraged Weighted Loss for Partial Label Learning
Hongwei Wen, Jingyi Cui, Hanyuan Hang +3
As an important branch of weakly supervised learning, partial label learning deals with data where each instance is assigned with a set of candidate labels, whereas only one of the…
Gradient Boosted Binary Histogram Ensemble for Large-scale Regression
Hanyuan Hang, Tao Huang, Yuchao Cai +2
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 histo…