no code implementations • 16 Sep 2023 • Junren Chen, Shuai Huang, Michael K. Ng, Zhaoqiang Liu
The problem of recovering a signal $\boldsymbol{x} \in \mathbb{R}^n$ from a quadratic system $\{y_i=\boldsymbol{x}^\top\boldsymbol{A}_i\boldsymbol{x},\ i=1,\ldots, m\}$ with full-rank matrices $\boldsymbol{A}_i$ frequently arises in applications such as unassigned distance geometry and sub-wavelength imaging.
1 code implementation • ICCV 2023 • Dingkang Yang, Shuai Huang, Zhi Xu, Zhenpeng Li, Shunli Wang, Mingcheng Li, Yuzheng Wang, Yang Liu, Kun Yang, Zhaoyu Chen, Yan Wang, Jing Liu, Peixuan Zhang, Peng Zhai, Lihua Zhang
Driver distraction has become a significant cause of severe traffic accidents over the past decade.
no code implementations • 5 Jul 2023 • Shuai Huang, James J. Lah, Jason W. Allen, Deqiang Qiu
Purpose: To achieve automatic hyperparameter estimation for the joint recovery of quantitative MR images, we propose a Bayesian formulation of the reconstruction problem that incorporates the signal model.
1 code implementation • CVPR 2023 • Dingkang Yang, Zhaoyu Chen, Yuzheng Wang, Shunli Wang, Mingcheng Li, Siao Liu, Xiao Zhao, Shuai Huang, Zhiyan Dong, Peng Zhai, Lihua Zhang
However, a long-overlooked issue is that a context bias in existing datasets leads to a significantly unbalanced distribution of emotional states among different context scenarios.
no code implementations • 26 Sep 2022 • Zepeng Huo, Taowei Ji, Yifei Liang, Shuai Huang, Zhangyang Wang, Xiaoning Qian, Bobak Mortazavi
We argue that traditional methods have rarely made use of both times-series dynamics of the data as well as the relatedness of the features from different sensors.
1 code implementation • 29 Jul 2022 • Shuai Huang, James J. Lah, Jason W. Allen, Deqiang Qiu
Purpose: For quantitative susceptibility mapping (QSM), the lack of ground-truth in clinical settings makes it challenging to determine suitable parameters for the dipole inversion.
no code implementations • 23 Jul 2022 • Zepeng Huo, Xiaoning Qian, Shuai Huang, Zhangyang Wang, Bobak J. Mortazavi
Medical events of interest, such as mortality, often happen at a low rate in electronic medical records, as most admitted patients survive.
1 code implementation • 6 Jul 2022 • Shuai Huang, Mona Zehni, Ivan Dokmanić, Zhizhen Zhao
Unknown-view tomography (UVT) reconstructs a 3D density map from its 2D projections at unknown, random orientations.
1 code implementation • 20 May 2022 • Shuai Huang, Deqiang Qiu, Trac D. Tran
In AMP, the signal of interest is assumed to follow certain prior distribution with unknown parameters.
no code implementations • 31 Mar 2022 • Randy Ardywibowo, Shahin Boluki, Zhangyang Wang, Bobak Mortazavi, Shuai Huang, Xiaoning Qian
At its core is an implicit variational distribution on binary gates that are dependent on previous observations, which will select the next subset of features to observe.
no code implementations • 9 Mar 2021 • Shuai Huang, James J. Lah, Jason W. Allen, Deqiang Qiu
In order to achieve better image quality and avoid manual parameter tuning, we propose a probabilistic Bayesian approach to recover $R_2^*$ map and phase images for quantitative susceptibility mapping (QSM), while allowing automatic parameter estimation from undersampled data.
no code implementations • 1 Jan 2021 • Randy Ardywibowo, Shahin Boluki, Zhangyang Wang, Bobak J Mortazavi, Shuai Huang, Xiaoning Qian
In many machine learning tasks, input features with varying degrees of predictive capability are usually acquired at some cost.
no code implementations • 4 Aug 2020 • Shuai Huang, James J. Lah, Jason W. Allen, Deqiang Qiu
Magnetic resonance (MR)-$T_2^*$ mapping is widely used to study hemorrhage, calcification and iron deposition in various clinical applications, it provides a direct and precise mapping of desired contrast in the tissue.
no code implementations • 29 Jul 2020 • Shuai Huang, Deqiang Qiu, Trac D. Tran
The proposed approach leads to a much simpler parameter estimation method, allowing us to work with the quantization noise model directly.
Quantization Information Theory Signal Processing Information Theory
no code implementations • 3 Mar 2020 • Zepeng Huo, Arash Pakbin, Xiaohan Chen, Nathan Hurley, Ye Yuan, Xiaoning Qian, Zhangyang Wang, Shuai Huang, Bobak Mortazavi
Activity recognition in wearable computing faces two key challenges: i) activity characteristics may be context-dependent and change under different contexts or situations; ii) unknown contexts and activities may occur from time to time, requiring flexibility and adaptability of the algorithm.
no code implementations • 21 Feb 2019 • Aven Samareh, Shuai Huang
In this paper, we aim at filling this gap by developing an uncertainty quantification based contemporaneous longitudinal index, named UQ-CHI, with a particular focus on continuous patient monitoring of degenerative conditions.
1 code implementation • 14 Feb 2019 • Shuai Huang, Sidharth Gupta, Ivan Dokmanić
We tackle the problem of recovering a complex signal $\boldsymbol x\in\mathbb{C}^n$ from quadratic measurements of the form $y_i=\boldsymbol x^*\boldsymbol A_i\boldsymbol x$, where $\boldsymbol A_i$ is a full-rank, complex random measurement matrix whose entries are generated from a rotation-invariant sub-Gaussian distribution.
Information Theory Information Theory
no code implementations • 8 Jan 2019 • Randy Ardywibowo, Guang Zhao, Zhangyang Wang, Bobak Mortazavi, Shuai Huang, Xiaoning Qian
This power-efficient sensing scheme can be achieved by deciding which group of sensors to use at a given time, requiring an accurate characterization of the trade-off between sensor energy usage and the uncertainty in ignoring certain sensor signals while monitoring.
1 code implementation • 25 Nov 2018 • Mona Zehni, Shuai Huang, Ivan Dokmanić, Zhizhen Zhao
For a point source model, we show that these features reveal geometric information about the model such as the radial and pairwise distances.
no code implementations • 15 Jun 2018 • Shaogang Ren, Jianhua Z. Huang, Shuai Huang, Xiaoning Qian
More critically, SAIF has the safe guarantee as it has the convergence guarantee to the optimal solution to the original full LASSO problem.
1 code implementation • 6 Apr 2018 • Shuai Huang, Ivan Dokmanić
Our method is the first practical approach to solve the large-scale noisy beltway problem where the points lie on a loop.
no code implementations • 18 Mar 2018 • Ke Ren, Haichuan Yang, Yu Zhao, Mingshan Xue, Hongyu Miao, Shuai Huang, Ji Liu
The positive-unlabeled (PU) classification is a common scenario in real-world applications such as healthcare, text classification, and bioinformatics, in which we only observe a few samples labeled as "positive" together with a large volume of "unlabeled" samples that may contain both positive and negative samples.
no code implementations • 29 Nov 2017 • Aven Samareh, Yan Jin, Zhangyang Wang, Xiangyu Chang, Shuai Huang
We present our preliminary work to determine if patient's vocal acoustic, linguistic, and facial patterns could predict clinical ratings of depression severity, namely Patient Health Questionnaire depression scale (PHQ-8).
no code implementations • 10 Sep 2017 • Bowen Cheng, Zhangyang Wang, Zhaobin Zhang, Zhu Li, Ding Liu, Jianchao Yang, Shuai Huang, Thomas S. Huang
Emotion recognition from facial expressions is tremendously useful, especially when coupled with smart devices and wireless multimedia applications.
no code implementations • 12 Nov 2016 • Chuyang Ke, Yan Jin, Heather Evans, Bill Lober, Xiaoning Qian, Ji Liu, Shuai Huang
Since existing prediction models of SSI have quite limited capacity to utilize the evolving clinical data, we develop the corresponding solution to equip these mHealth tools with decision-making capabilities for SSI prediction with a seamless assembly of several machine learning models to tackle the analytic challenges arising from the spatial-temporal data.
no code implementations • 14 Aug 2016 • Zhangyang Wang, Shiyu Chang, Qing Ling, Shuai Huang, Xia Hu, Honghui Shi, Thomas S. Huang
With the agreement of my coauthors, I Zhangyang Wang would like to withdraw the manuscript "Stacked Approximated Regression Machine: A Simple Deep Learning Approach".
no code implementations • CVPR 2016 • Haichuan Yang, Yijun Huang, Lam Tran, Ji Liu, Shuai Huang
In this paper, we proposed a general bilevel exclusive sparsity formulation to pursue the diversity by restricting the overall sparsity and the sparsity in each group.
no code implementations • NeurIPS 2011 • Shuai Huang, Jing Li, Jieping Ye, Teresa Wu, Kewei Chen, Adam Fleisher, Eric Reiman
This is especially true for early AD, at which stage the disease-related regions are most likely to be weak-effect regions that are difficult to be detected from a single modality alone.
no code implementations • NeurIPS 2009 • Shuai Huang, Jing Li, Liang Sun, Jun Liu, Teresa Wu, Kewei Chen, Adam Fleisher, Eric Reiman, Jieping Ye
Recent advances in neuroimaging techniques provide great potentials for effective diagnosis of Alzheimer’s disease (AD), the most common form of dementia.