7 citations · 24 across the 17 of their papers we have counts for
18 papers
Penguin data reanalyzed via Computational Taxonomy
Thomas B. Michelon, Avidane C. Caballero, Hsieh Fushing
We employ Computational Taxonomy (CT) to reanalyze the penguin data set penguins_lter by validating and addressing two biological issues: Sexual Size Dimorphism (SSD) and mate-sele…
Design of Experiment in Complex Systems based on Computational Taxonomy
Eric Goldman, Fushing Hsieh
Via Computational Taxonomy (CT), we develop Design of Experiment(DoE) based on rigorously redefined constituting ingredients of complex system dynamics: randomness, nonlinearity an…
Structure-Preserving Visualization of Complex Systems through Discrete Approximation: An Application to Argo Data
Shang-Ying Shiu, Fushing Hsieh, Ting-Li Chen
This paper presents a framework for constructing structure-preserving representations of complex systems through discrete approximation, and demonstrates its use in studying the ve…
Unraveling heterogeneity of ADNI's time-to-event data using conditional entropy Part-I: Cross-sectional study
Shuting Liao, Fushing Hsieh
Through Alzheimer's Disease Neuroimaging Initiative (ADNI), time-to-event data: from the pre-dementia state of mild cognitive impairment (MCI) to the diagnosis of Alzheimer's disea…
Learned practical guidelines for evaluating Conditional Entropy and Mutual Information in discovering major factors of response-vs-covariate dynamics
Ting-Li Chen, Hsieh Fushing, Elizabeth P. Chou
We reformulate and reframe a series of increasingly complex parametric statistical topics into a framework of response-vs-covariate (Re-Co) dynamics that is described without any e…
Multiscale major factor selections for complex system data with structural dependency and heterogeneity
Hsieh Fushing, Elizabeth Chou, Ting-Li Chen
Based on structured data derived from large complex systems, we computationally further develop and refine a major factor selection protocol by accommodating structural dependency…
An Encoding Approach for Stable Change Point Detection
Xiaodong Wang, Fushing Hsieh
Without imposing prior distributional knowledge underlying multivariate time series of interest, we propose a nonparametric change-point detection approach to estimate the number o…
Coarse- and fine-scale geometric information content of Multiclass Classification and implied Data-driven Intelligence
Fushing Hsieh, Xiaodong Wang
Under any Multiclass Classification (MCC) setting defined by a collection of labeled point-cloud specified by a feature-set, we extract only stochastic partial orderings from all p…
Discovering Multiple Phases of Dynamics by Dissecting Multivariate Time Series
Xiaodong Wang, Fushing Hsieh
We proposed a data-driven approach to dissect multivariate time series in order to discover multiple phases underlying dynamics of complex systems. This computing approach is devel…
Unraveling S&P500 stock volatility and networks -- An encoding-and-decoding approach
Xiaodong Wang, Fushing Hsieh
Volatility of financial stock is referring to the degree of uncertainty or risk embedded within a stock's dynamics. Such risk has been received huge amounts of attention from diver…
Categorical exploratory data analysis on goodness-of-fit issues
Sabrina Enriquez, Fushing Hsieh
If the aphorism "All models are wrong"- George Box, continues to be true in data analysis, particularly when analyzing real-world data, then we should annotate this wisdom with vis…
Extreme-K categorical samples problem
Elizabeth Chou, Catie McVey, Yin-Chen Hsieh +2
With histograms as its foundation, we develop Categorical Exploratory Data Analysis (CEDA) under the extreme- sample problem, and illustrate its universal applicability through…
Color-complexity enabled exhaustive color-dots identification and spatial patterns testing in images
Shuting Liao, Li-Yu Liu, Ting-An Chen +2
Targeted color-dots with varying shapes and sizes in images are first exhaustively identified, and then their multiscale 2D geometric patterns are extracted for testing spatial uni…
Categorical Exploratory Data Analysis: From Multiclass Classification and Response Manifold Analytics perspectives of baseball pitching dynamics
Fushing Hsieh, Elizabeth P. Chou
From two coupled Multiclass Classification (MCC) and Response Manifold Analytics (RMA) perspectives, we develop Categorical Exploratory Data Analysis (CEDA) on PITCHf/x database fo…
From learning gait signatures of many individuals to reconstructing gait dynamics of one single individual
Fushing Hsieh, Xiaodong Wang
Based on the same databases, we computationally address two seemingly highly related, in fact drastically distinct, questions via computational data-driven algorithms: 1) how to pr…
Information of Epileptic Mechanism and its Systemic Change-points in a Zebrafish's Brain-wide Calcium Imaging Video Data
Jingyi Zheng, Fushing Hsieh
The epileptic mechanism is postulated as that an animal's neurons gradually diminish their inhibition function coupled with enhanced excitation when an epileptic event is approachi…
Coupling geometry on binary bipartite networks: hypotheses testing on pattern geometry and nestedness
Jiahui Guan, Hsieh Fushing
Upon a matrix representation of a binary bipartite network, via the permutation invariance, a coupling geometry is computed to approximate the minimum energy macrostate of a networ…
Graphic displays of MLB pitching mechanics and its evolutions in PITCHf/x data
Fushing Hsieh, Kevin Fujii, Tania Roy +2
Systemic and idiosyncratic patterns in pitching mechanics of 24 top starting pitchers in Major League Baseball (MLB) are extracted and discovered from PITCHf/x database. These evol…