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653 results on '"Li, Yuanxin"'

6. CDBMA: Community Detection in Heterogeneous Networks Based on Multi-attention Mechanism

Author

Li, Yuanxin, Wu, Zhixiang, Wang, Zhenyu, Li, Ping, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Wu, Feng, editor, Huang, Xuanjing, editor, He, Xiangnan, editor, Tang, Jiliang, editor, Zhao, Shu, editor, Li, Daifeng, editor, and Zhang, Jing, editor

Published
2024
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21. Beyond Procrustes: Balancing-Free Gradient Descent for Asymmetric Low-Rank Matrix Sensing

Author

Ma, Cong, Li, Yuanxin, and Chi, Yuejie

Subjects
Electrical Engineering and Systems Science - Signal Processing, Computer Science - Information Theory, Statistics - Machine Learning
Abstract

Low-rank matrix estimation plays a central role in various applications across science and engineering. Recently, nonconvex formulations based on matrix factorization are provably solved by simple gradient descent algorithms with strong computational and statistical guarantees. However, when the low-rank matrices are asymmetric, existing approaches rely on adding a regularization term to balance the scale of the two matrix factors which in practice can be removed safely without hurting the performance when initialized via the spectral method. In this paper, we provide a theoretical justification to this for the matrix sensing problem, which aims to recover a low-rank matrix from a small number of linear measurements. As long as the measurement ensemble satisfies the restricted isometry property, gradient descent -- in conjunction with spectral initialization -- converges linearly without the need of explicitly promoting balancedness of the factors; in fact, the factors stay balanced automatically throughout the execution of the algorithm. Our analysis is based on analyzing the evolution of a new distance metric that directly accounts for the ambiguity due to invertible transforms, and might be of independent interest., Comment: To appear on IEEE Trans. on Signal Processing

Published
2021
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31. Making of Children’s Bed Brochure Based on Augmented Reality

Author

Zhang, Xuezhao, Si, Zhanjun, Li, Yuanxin, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Zhao, Pengfei, editor, Ye, Zhuangzhi, editor, Xu, Min, editor, Yang, Li, editor, Zhang, Linghao, editor, and Yan, Shu, editor

Published
2022
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35. Nonconvex Matrix Factorization from Rank-One Measurements

Author

Li, Yuanxin, Ma, Cong, Chen, Yuxin, and Chi, Yuejie

Subjects
Computer Science - Information Theory, Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

We consider the problem of recovering low-rank matrices from random rank-one measurements, which spans numerous applications including covariance sketching, phase retrieval, quantum state tomography, and learning shallow polynomial neural networks, among others. Our approach is to directly estimate the low-rank factor by minimizing a nonconvex quadratic loss function via vanilla gradient descent, following a tailored spectral initialization. When the true rank is small, this algorithm is guaranteed to converge to the ground truth (up to global ambiguity) with near-optimal sample complexity and computational complexity. To the best of our knowledge, this is the first guarantee that achieves near-optimality in both metrics. In particular, the key enabler of near-optimal computational guarantees is an implicit regularization phenomenon: without explicit regularization, both spectral initialization and the gradient descent iterates automatically stay within a region incoherent with the measurement vectors. This feature allows one to employ much more aggressive step sizes compared with the ones suggested in prior literature, without the need of sample splitting., Comment: 34 pages

Published
2018

36. Electron spin density matching for cross-effect dynamic nuclear polarization

Author

Li, Yuanxin, Equbal, Asif, Tagami, Kan, and Han, Songi

Subjects
Chemical Sciences, Organic Chemistry, Chemical sciences, Engineering
Abstract

A new design principle for a mixed broad (TEMPO) and narrow (Trityl) line radical to boost the dynamic nuclear polarization efficiency is electron spin density matching, suggesting a polarizing agent of one Trityl tethered to at least two TEMPO moieties.

Published
2019

44. Nonconvex Low-Rank Matrix Recovery with Arbitrary Outliers via Median-Truncated Gradient Descent

Author

Li, Yuanxin, Chi, Yuejie, Zhang, Huishuai, and Liang, Yingbin

Subjects
Computer Science - Information Theory, Statistics - Machine Learning
Abstract

Recent work has demonstrated the effectiveness of gradient descent for directly recovering the factors of low-rank matrices from random linear measurements in a globally convergent manner when initialized properly. However, the performance of existing algorithms is highly sensitive in the presence of outliers that may take arbitrary values. In this paper, we propose a truncated gradient descent algorithm to improve the robustness against outliers, where the truncation is performed to rule out the contributions of samples that deviate significantly from the {\em sample median} of measurement residuals adaptively in each iteration. We demonstrate that, when initialized in a basin of attraction close to the ground truth, the proposed algorithm converges to the ground truth at a linear rate for the Gaussian measurement model with a near-optimal number of measurements, even when a constant fraction of the measurements are arbitrarily corrupted. In addition, we propose a new truncated spectral method that ensures an initialization in the basin of attraction at slightly higher requirements. We finally provide numerical experiments to validate the superior performance of the proposed approach., Comment: 30 pages, 3 figures

Published
2017

49. Truncated Cross Effect Dynamic Nuclear Polarization: An Overhauser Effect Doppelgänger.

Author

Equbal, Asif, Li, Yuanxin, Leavesley, Alisa, Huang, Shengdian, Rajca, Suchada, Rajca, Andrzej, and Han, Songi

Abstract

The discovery of a truncated cross-effect (CE) in dynamic nuclear polarization (DNP) NMR that has the features of an Overhauser-effect DNP (OE-DNP) is reported here. The apparent OE-DNP, where minimal μw power achieved optimum enhancement, was observed when doping Trityl-OX063 with a pyrroline nitroxide radical that possesses electron-withdrawing tetracarboxylate substituents (tetracarboxylate-ester-pyrroline or TCP) in vitrified water/glycerol at 6.9 T and at 3.3 to 85 K, in apparent contradiction to expectations. While the observations are fully consistent with OE-DNP, we discover that a truncated cross-effect ( tCE) is the underlying mechanism, owing to TCPs shortened T1e. We take this observation as a guideline and demonstrate that a crossover from CE to tCE can be replicated by simulating the CE of a narrow-line (Trityl-OX063) and a broad-line (TCP) radical pair, with a significantly shortened T1e of the broad-line radical.

Published
2018

50. Surface chemical heterogeneity modulates silica surface hydration.

Author

Schrader, Alex, Monroe, Jacob, Sheil, Ryan, Dobbs, Howard, Keller, Timothy, Li, Yuanxin, Jain, Sheetal, Shell, M, Israelachvili, Jacob, and Han, Songi

Subjects
hydration dynamics, hydrophobicity, silica, surface forces, water
Abstract

An in-depth knowledge of the interaction of water with amorphous silica is critical to fundamental studies of interfacial hydration water, as well as to industrial processes such as catalysis, nanofabrication, and chromatography. Silica has a tunable surface comprising hydrophilic silanol groups and moderately hydrophobic siloxane groups that can be interchanged through thermal and chemical treatments. Despite extensive studies of silica surfaces, the influence of surface hydrophilicity and chemical topology on the molecular properties of interfacial water is not well understood. In this work, we controllably altered the surface silanol density, and measured surface water diffusivity using Overhauser dynamic nuclear polarization (ODNP) and complementary silica-silica interaction forces across water using a surface forces apparatus (SFA). The results show that increased silanol density generally leads to slower water diffusivity and stronger silica-silica repulsion at short aqueous separations (less than ∼4 nm). Both techniques show sharp changes in hydration properties at intermediate silanol densities (2.0-2.9 nm-2). Molecular dynamics simulations of model silica-water interfaces corroborate the increase in water diffusivity with silanol density, and furthermore show that even on a smooth and crystalline surface at a fixed silanol density, adjusting the spatial distribution of silanols results in a range of surface water diffusivities spanning ∼10%. We speculate that a critical silanol cluster size or connectivity parameter could explain the sharp transition in our results, and can modulate wettability, colloidal interactions, and surface reactions, and thus is a phenomenon worth further investigation on silica and chemically heterogeneous surfaces.

Published
2018

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