Posts by Collection

testOTM

[GitHub] [Vignette]

testOTM is an R package that computes multivariate ranks and quantiles defined through the theory of optimal transports. It also provides several applications of these statistics, most notably the two-sample multivariate goodness-of-fit testing. The user can use this package to visualize the optimal transport map between uniform probability measure and any data-set. The following interactive plot showcases an optimal transport map between $U[0,1]^3$ and a trivariate Gaussian sample:

alocv

[GitHub] [arXiv] [Blog post]

alocv is an R package that implement the approximate leave-one-out (ALO) cross-validation strategy for common regressors in an efficient way. Leave-one-out cross-validation (LOOCV) is an appealing method for parameter tuning. However, its high computational cost (requiring fitting the model $n$ times) often makes it infeasible in application. Our proposed method approximates the LOOCV estimations using only the full data fit and siginificantly reduced the time needed for risk estimation.

orthoDr: Semiparametric Dimension Reduction via Orthogonality Constrained Optimization

Published in The R Journal, 2019

[Link] [Preprint] [R Package]

Citation: Ruoqing Zhu, Jiyang Zhang, Ruilin Zhao, Peng Xu, Wenzhuo Zhou, Xin Zhang. (2019). orthoDr: Semiparametric Dimension Reduction via Orthogonality Constrained Optimization. The R Journal.

Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions

Published in INFORMS Data Mining and Decision Analysis Workshop, 2019

[Link] [R Package]

Citation: Wenda Zhou, Shuaiwen Wang, Peng Xu, Haiho Lu, Arian Maleki, Vahab Mirrokni. (2019). Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions. 2019 INFORMS Workshop on Data Mining and Decision Analytics.

Generative quantum machine learning via denoising diffusion probabilistic models

Submitted, 2023

[Preprint]

Citation: Bingzhi Zhang, Peng Xu, Xiaohui Chen, Quntao Zhuang. (2023). Generative quantum machine learning via denoising diffusion probabilistic models.

Talk 1 on Relevant Topic in Your Field

Published: March 01, 2012

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Tutorial 1 on Relevant Topic in Your Field

Published: March 01, 2013

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Talk 2 on Relevant Topic in Your Field

Published: February 01, 2014

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Conference Proceeding talk 3 on Relevant Topic in Your Field

Published: March 01, 2014

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Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015

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