Publications

PACE: A Large-Scale Dataset with Pose Annotations in Cluttered Environments
Yang You, Kai Xiong, Zhening Yang, Zhengxiang Huang, Junwei Zhou, Ruoxi Shi, Zhou Fang, Adam W Harley, Leonidas Guibas, Cewu Lu
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Structured Graph Reconstruction for Scalabl Clustering
we propose a method called Orthogonal and Nonnegative Graph Reconstruction (ONGR) for large scale clustering. This is an journal extension of the work published in conference IJCAI-2017.
Junwei Han, Kai Xiong, Feiping Nie, Xuelong Li
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Structured Graph Reconstruction for Scalabl Clustering
Regularized and Constrained Self-representation for Robust Feature Selection
Feature selection is an important topic in data mining. In this paper, we focus on the problem in unsupervised scenario, which is …
Kai Xiong, Feiping Nie, Junwei Han
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Regularized and Constrained Self-representation for Robust Feature Selection
Orthogonal and Nonnegative Graph Reconstruction for Large Scale Clustering
We propose a novel clustering approach denoted by orthogonal and nonnegative graph reconstruction (ONGR) that scales linearly with the data size.
Junwei Han, Kai Xiong, Feiping Nie
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Orthogonal and Nonnegative Graph Reconstruction for Large Scale Clustering
Linear Manifold Regularization with Adaptive Graph for Semi-supervised Dimensionality Reduction
We propose a novel approach called linear manifold regularization with adaptive graph (LMRAG) for semi-supervised dimensionality reduction.
Kai Xiong, Feiping Nie, Junwei Han
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Linear Manifold Regularization with Adaptive Graph for Semi-supervised Dimensionality Reduction
Robust and Sparse Fuzzy K-Means Clustering
The partition-based clustering algorithms, like KMeans and fuzzy K-Means, are most widely and successfully used in data mining in the …
Jinglin Xu, Junwei Han, Kai Xiong, Feiping Nie
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Robust and Sparse Fuzzy K-Means Clustering