Search Results for author: Hau-Tieng Wu

Found 28 papers, 6 papers with code

Discovery of temporal structure intricacy in arterial blood pressure waveforms representing acuity of liver transplant and forecasting short term surgical outcome via unsupervised manifold learning

no code implementations21 Sep 2021 Shen-Chih Wang, Chien-Kun Ting, Cheng-Yen Chen, Chin-Su Liu, Niang-Cheng Lin, Che-Chuan Loon, Hau-Tieng Wu, Yu-Ting Lin

Conclusions: The ABP waveform evolution intricacy in the presurgical phase reflects recipients' acuity condition while that in the neohepatic phase reveal the short-term surgical outcome calculated from laboratory data in postoperative day 7-10.

Central and Non-central Limit Theorems arising from the Scattering Transform and its Neural Activation Generalization

no code implementations21 Nov 2020 Gi-Ren Liu, Yuan-Chung Sheu, Hau-Tieng Wu

On the whole, NAST is a transform that comprises a sequence of ``neural processing units'', each of which applies a high pass filter to the input from the previous layer followed by a composition with a nonlinear function as the output to the next neuron.

Time Series

Phase transition of graph Laplacian of high dimensional noisy random point cloud

no code implementations21 Nov 2020 Xiucai Ding, Hau-Tieng Wu

We systematically explore the spectral distribution of kernel-based graph Laplacian constructed from high dimensional and noisy random point cloud in the nonnull setup.

Convergence of Graph Laplacian with kNN Self-tuned Kernels

no code implementations3 Nov 2020 Xiuyuan Cheng, Hau-Tieng Wu

This paper proves the convergence of graph Laplacian operator $L_N$ to manifold (weighted-)Laplacian for a new family of kNN self-tuned kernels $W^{(\alpha)}_{ij} = k_0( \frac{ \| x_i - x_j \|^2}{ \epsilon \hat{\rho}(x_i) \hat{\rho}(x_j)})/\hat{\rho}(x_i)^\alpha \hat{\rho}(x_j)^\alpha$, where $\hat{\rho}$ is the estimated bandwidth function {by kNN}, and the limiting operator is also parametrized by $\alpha$.

Decomposing non-stationary signals with time-varying wave-shape functions

1 code implementation14 Oct 2020 Marcelo A. Colominas, Hau-Tieng Wu

We propose a novel {\em nonlinear regression scheme} to robustly decompose a signal into its constituting multiple oscillatory components with time-varying frequency, amplitude and wave-shape function.

Time Series

Graph based Gaussian processes on restricted domains

no code implementations14 Oct 2020 David B Dunson, Hau-Tieng Wu, Nan Wu

The GL is constructed from a kernel which depends only on the Euclidean coordinates of the inputs.

Gaussian Processes

Denoising Click-evoked Otoacoustic Emission Signals by Optimal Shrinkage

no code implementations1 Sep 2020 Tzu-Chi Liu, Yi-Wen Liu, Hau-Tieng Wu

The sOS achieved an SNR enhancement of 2 to 3 dB in simulation, and demonstrated capability to enhance the SNR in real recordings when the SNR achieved by the BM was below 0 dB.

Denoising

Strong Uniform Consistency with Rates for Kernel Density Estimators with General Kernels on Manifolds

no code implementations13 Jul 2020 Hau-Tieng Wu, Nan Wu

When analyzing modern machine learning algorithms, we may need to handle kernel density estimation (KDE) with intricate kernels that are not designed by the user and might even be irregular and asymmetric.

Density Estimation

Unsupervised ensembling of multiple software sensors: a new approach for electrocardiogram-derived respiration using one or two channels

no code implementations23 Jun 2020 John Malik, Yu-Ting Lin, Ronen Talmon, Hau-Tieng Wu

While several electrocardiogram-derived respiratory (EDR) algorithms have been proposed to extract breathing activity from a single-channel ECG signal, conclusively identifying a superior technique is challenging.

A persistent homology approach to heart rate variability analysis with an application to sleep-wake classification

1 code implementation9 Aug 2019 Yu-Min Chung, Chuan-Shen Hu, Yu-Lun Lo, Hau-Tieng Wu

The first step is capturing the shapes of time series from two different aspects -- {the PH's and hence persistence diagrams of its} sub-level set and Taken's lag map.

General Classification Heart Rate Variability +1

Non-contact photoplethysmogram and instantaneous heart rate estimation from infrared face video

1 code implementation14 Feb 2019 Natalia Martinez, Martin Bertran, Guillermo Sapiro, Hau-Tieng Wu

One way to avoid these constraints is using infrared cameras, allowing the monitoring of iHR under low light conditions.

Heart rate estimation

When Locally Linear Embedding Hits Boundary

no code implementations11 Nov 2018 Hau-Tieng Wu, Nan Wu

Based on the Riemannian manifold model, we study the asymptotical behavior of a widely applied unsupervised learning algorithm, locally linear embedding (LLE), when the point cloud is sampled from a compact, smooth manifold with boundary.

Statistics Theory Statistics Theory 62-07

Solving Jigsaw Puzzles By the Graph Connection Laplacian

3 code implementations7 Nov 2018 Vahan Huroyan, Gilad Lerman, Hau-Tieng Wu

The main contribution of this work is a method for recovering the rotations of the pieces when both shuffles and rotations are unknown.

Unexpected sawtooth artifact in beat-to-beat pulse transit time measured from patient monitor data

no code implementations27 Aug 2018 Yu-Ting Lin, Yu-Lun Lo, Chen-Yun Lin, Hau-Tieng Wu, Martin G. Frasch

However, in this setup the data calibration issue is often not discussed and, rather, implicitly assumed, while the clinical monitors might not be designed for the data analysis purpose.

Photoplethysmography (PPG)

Can a composite heart rate variability biomarker shed new insights about autism spectrum disorder in school-aged children?

1 code implementation24 Aug 2018 Martin G. Frasch, Chao Shen, Hau-Tieng Wu, Alexander Mueller, Emily Neuhaus, Raphael A. Bernier, Dana Kamara, Theodore P. Beauchaine

High-frequency heart rate variability (HRV) has identified parasympathetic nervous system alterations in autism spectrum disorder (ASD).

Quantitative Methods Neurons and Cognition

Sleep-wake classification via quantifying heart rate variability by convolutional neural network

no code implementations1 Aug 2018 John Malik, Yu-Lun Lo, Hau-Tieng Wu

This result advocates for an effective and scalable method for recognizing changes in physiological state using non-invasive heart rate monitoring.

General Classification Heart Rate Variability

Efficient fetal-maternal ECG signal separation from two channel maternal abdominal ECG via diffusion-based channel selection

no code implementations7 Feb 2017 Ruilin Li, Martin G. Frasch, Hau-Tieng Wu

There is a need for affordable, widely deployable maternal-fetal ECG monitors to improve maternal and fetal health during pregnancy and delivery.

Diffusion-based nonlinear filtering for multimodal data fusion with application to sleep stage assessment

no code implementations13 Jan 2017 Ori Katz, Ronen Talmon, Yu-Lun Lo, Hau-Tieng Wu

We show that without prior knowledge on the different modalities and on the measured system, our method gives rise to a data-driven representation that is well correlated with the underlying sleep process and is robust to noise and sensor-specific effects.

Extract fetal ECG from single-lead abdominal ECG by de-shape short time Fourier transform and nonlocal median

no code implementations9 Sep 2016 Su Li, Hau-Tieng Wu

The multiple fundamental frequency detection problem and the source separation problem from a single-channel signal containing multiple oscillatory components and a nonstationary noise are both challenging tasks.

Latent common manifold learning with alternating diffusion: analysis and applications

1 code implementation30 Jan 2016 Ronen Talmon, Hau-Tieng Wu

The analysis of data sets arising from multiple sensors has drawn significant research attention over the years.

Connection graph Laplacian methods can be made robust to noise

no code implementations23 May 2014 Noureddine El Karoui, Hau-Tieng Wu

Recently, several data analytic techniques based on connection graph laplacian (CGL) ideas have appeared in the literature.

Graph connection Laplacian and random matrices with random blocks

no code implementations1 Oct 2013 Noureddine El Karoui, Hau-Tieng Wu

Graph connection Laplacian (GCL) is a modern data analysis technique that is starting to be applied for the analysis of high dimensional and massive datasets.

Spectral Convergence of the connection Laplacian from random samples

no code implementations7 Jun 2013 Amit Singer, Hau-Tieng Wu

We prove that the eigenvectors and eigenvalues of these Laplacians converge in the limit of infinitely many independent random samples.

Dimensionality Reduction

Embedding Riemannian Manifolds by the Heat Kernel of the Connection Laplacian

no code implementations18 May 2013 Hau-Tieng Wu

Given a class of closed Riemannian manifolds with prescribed geometric conditions, we introduce an embedding of the manifolds into $\ell^2$ based on the heat kernel of the Connection Laplacian associated with the Levi-Civita connection on the tangent bundle.

Cannot find the paper you are looking for? You can Submit a new open access paper.