activity
20182020
most citedEnsemble Pruning based on Objection Maximization with a General Distributed Framework

56 citations · 73 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2020

Human Activity Recognition based on Dynamic Spatio-Temporal Relations

Zhenyu Liu, Yaqiang Yao, Yan Liu +4

Human activity, which usually consists of several actions, generally covers interactions among persons and or objects. In particular, human actions involve certain spatial and temp…

cs.LG2019★ 1 cited

Use Short Isometric Shapelets to Accelerate Binary Time Series Classification

Weibo Shu, Yaqiang Yao, Shengfei Lyu +2

In the research area of time series classification, the ensemble shapelet transform algorithm is one of state-of-the-art algorithms for classification. However, its high time compl…

cs.LG2019★ 4 cited

Bayesian Optimization with Directionally Constrained Search

Yang Li, Yaqiang Yao

Bayesian optimization offers a flexible framework to optimize an objective function that is expensive to be evaluated. A Bayesian optimizer iteratively queries the function values…

cs.LG2018★ 12 cited

Multiple Kernel -Means Clustering by Selecting Representative Kernels

Yaqiang Yao, Huanhuan Chen

To cluster data that are not linearly separable in the original feature space, -means clustering was extended to the kernel version. However, the performance of kernel -means…

cs.CV2018

Skeleton-based Activity Recognition with Local Order Preserving Match of Linear Patches

Yaqiang Yao, Yan Liu, Huanhuan Chen

Human activity recognition has drawn considerable attention recently in the field of computer vision due to the development of commodity depth cameras, by which the human activity…

cs.LG2018★ 56 cited

Ensemble Pruning based on Objection Maximization with a General Distributed Framework

Yijun Bian, Yijun Wang, Yaqiang Yao +1

Ensemble pruning, selecting a subset of individual learners from an original ensemble, alleviates the deficiencies of ensemble learning on the cost of time and space. Accuracy and…