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- Guangcan Liu, Zhouchen Lin, Shuicheng Yan, Ju Sun, Yong Yu, Yuliang Ma
- IEEE Transactions on Pattern Analysis and Machine…
- 2013

In this paper, we address the subspace clustering problem. Given a set of data samples (vectors) approximately drawn from a union of multiple subspaces, our goal is to cluster the samples into their… (More)

- Ju Sun, Qing Qu, John Wright
- ISIT
- 2016

- Ju Sun, Qing Qu, John Wright
- IEEE Trans. Information Theory
- 2017

We consider the problem of recovering a complete (i.e., square and invertible) matrix $ A_{0}$ , from $ Y \in \mathbb R ^{n \times p}$ with $ Y = A_{0} X_{0}$ , provided $ X_{0}$ is sufficiently… (More)

- Yadong Mu, Ju Sun, Tony X. Han, Loong Fah Cheong, Shuicheng Yan
- ECCV
- 2010

Visual vocabulary construction is an integral part of the popular Bag-of-Features (BOF) model. When visual data scale up (in terms of the dimensionality of features or/and the number of samples),… (More)

- Yuzhao Ni, Ju Sun, Xiao-Tong Yuan, Shuicheng Yan, Loong Fah Cheong
- IEEE International Conference on Data Mining…
- 2010

Recently there is a line of research work proposing to employ Spectral Clustering (SC) to segment (group)\footnote{Throughout the paper, we use segmentation, clustering, and grouping, and their verb… (More)

- Ju Sun, Yadong Mu, Shuicheng Yan, Loong Fah Cheong
- IEEE International Conference on Multimedia and…
- 2010

Current research on visual action/activity analysis has mostly exploited appearance-based static feature descriptions, plus statistics of short-range motion fields. The deliberate ignorance of dense,… (More)

- Qing Qu, Ju Sun, John Wright
- IEEE Transactions on Information Theory
- 2014

Is it possible to find the sparsest vector (direction) in a generic subspace S ⊆ ℝp with dim(S) = n <; p? This problem can be considered a homogeneous variant of the sparse recovery problem and finds… (More)

- Ju Sun, Qing Qu, John Wright
- ArXiv
- 2015

In this note, we focus on smooth nonconvex optimization problems that obey: (1) all local minimizers are also global; and (2) around any saddle point or local maximizer, the objective has a negative… (More)

- Ju Sun, Qing Qu, John Wright
- International Conference on Sampling Theory and…
- 2015

We consider the problem of recovering a complete (i.e., square and invertible) dictionary A0, from Y = A0X0 with Y ϵ Rn×p. This recovery setting is central to the theoretical understanding of… (More)

- Ju Sun, Qing Qu, John Wright
- IEEE Transactions on Information Theory
- 2017

We consider the problem of recovering a complete (i.e., square and invertible) matrix <inline-formula> <tex-math notation="LaTeX">$ A_{0}$ </tex-math></inline-formula>, from <inline-formula>… (More)