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no code implementations • 2 Sep 2020 • Alfonso Landeros, Oscar Hernan Madrid Padilla, Hua Zhou, Kenneth Lange

The current paper studies the problem of minimizing a loss $f(\boldsymbol{x})$ subject to constraints of the form $\boldsymbol{D}\boldsymbol{x} \in S$, where $S$ is a closed set, convex or not, and $\boldsymbol{D}$ is a matrix that fuses parameters.

1 code implementation • 7 Jan 2020 • Seyoon Ko, Hua Zhou, Jin Zhou, Joong-Ho Won

To our knowledge, this is the first demonstration of the feasibility of penalized regression of survival outcomes at this scale.

Computation

no code implementations • 8 May 2019 • Bin Yang, Lin Yang, Xiaochun Li, Wenhan Zhang, Hua Zhou, Yequn Zhang, Yongxiong Ren, Yinbo Shi

Image retrieval utilizes image descriptors to retrieve the most similar images to a given query image.

no code implementations • 28 Nov 2018 • I-Cheng Tung, Aravind Krishnamoorthy, Sridhar Sadasivam, Hua Zhou, Qi Zhang, Kyle L. Seyler, Genevieve Clark, Ehren M. Mannebach, Clara Nyby, Friederike Ernst, Diling Zhu, James M. Glownia, Michael E. Kozina, Sanghoon Song, Silke Nelson, Hiroyuki Kumazoe, Fuyuki Shimojo, Rajiv K. Kalia, Priya Vashishta, Pierre Darancet, Tony F. Heinz, Aiichiro Nakano, Xiaodong Xu, Aaron M. Lindenberg, Haidan Wen

X-ray scattering is one of the primary tools to determine crystallographic configuration with atomic accuracy.

Materials Science

1 code implementation • 8 Nov 2018 • Joong-Ho Won, Hua Zhou, Kenneth Lange

Through a close inspection of Ky Fan's classical result (1949) on the variational formulation of the sum of largest eigenvalues of a symmetric matrix, and a semidefinite programming (SDP) relaxation of the latter, we first provide a simple method to certify global optimality of a given stationary point of OTSM.

Optimization and Control Computation

no code implementations • 24 Sep 2018 • Wei Hu, Weining Shen, Hua Zhou, Dehan Kong

We propose a novel linear discriminant analysis approach for the classification of high-dimensional matrix-valued data that commonly arises from imaging studies.

no code implementations • 17 Mar 2018 • Eric C. Chi, Brian R. Gaines, Will Wei Sun, Hua Zhou, Jian Yang

Our convex co-clustering (CoCo) estimator enjoys stability guarantees and its computational and storage costs are polynomial in the size of the data.

no code implementations • 7 Feb 2018 • Xin Chen, Hua Zhou, Yuxiang Gao, Yu Zhu

Therefore, MiMatrix intrinsically solves the bandwidth bottleneck of central node in parameter server framework that is widely used in distributed DL tasks.

no code implementations • 16 Aug 2017 • Aosen Wang, Hua Zhou, Wenyao Xu, Xin Chen

However, the capacity of deep neural network architecture is still a mystery to the researchers.

no code implementations • 8 May 2017 • Xin Chen, Yu Zhu, Hua Zhou, Liang Diao, Dongyan Wang

In this paper, we introduce a new and challenging large-scale food image dataset called "ChineseFoodNet", which aims to automatically recognizing pictured Chinese dishes.

1 code implementation • 28 Oct 2016 • Brian R. Gaines, Hua Zhou

We compare alternative computing strategies for solving the constrained lasso problem.

1 code implementation • 19 Apr 2016 • Kevin L. Keys, Hua Zhou, Kenneth Lange

If $f(\boldsymbol{x})$ is the loss function, and $C$ is the constraint set in a constrained minimization problem, then the proximal distance principle mandates minimizing the penalized loss $f(\boldsymbol{x})+\frac{\rho}{2}\mathop{dist}(x, C)^2$ and following the solution $\boldsymbol{x}_{\rho}$ to its limit as $\rho$ tends to $\infty$.

Optimization and Control 90C59, 90C26, 65K05

no code implementations • 16 Nov 2012 • Eric C. Chi, Hua Zhou, Kenneth Lange

The problem of minimizing a continuously differentiable convex function over an intersection of closed convex sets is ubiquitous in applied mathematics.

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