Search Results for author: Cheng-Shang Chang

Found 7 papers, 1 papers with code

Constructions and Comparisons of Pooling Matrices for Pooled Testing of COVID-19

no code implementations30 Sep 2020 Yi-Jheng Lin, Che-Hao Yu, Tzu-Hsuan Liu, Cheng-Shang Chang, Wen-Tsuen Chen

The family of PPoL matrices can dynamically adjust their column weights according to the prevalence rates and could be a better alternative than using a fixed pooling matrix.

Explainable, Stable, and Scalable Graph Convolutional Networks for Learning Graph Representation

no code implementations22 Sep 2020 Ping-En Lu, Cheng-Shang Chang

In addition to solving the network embedding problem, both proposed GCNs are capable of performing dimensionality reduction.

Dimensionality Reduction Network Embedding

A Time-dependent SIR model for COVID-19 with Undetectable Infected Persons

2 code implementations28 Feb 2020 Yi-Cheng Chen, Ping-En Lu, Cheng-Shang Chang, Tzu-Hsuan Liu

By relating the propagation probabilities in the IC model to the transmission rates and recovering rates in the SIR model, we show 2 approaches of social distancing that can lead to a reduction of $R_0$.

Time Series

A Reinforcement Learning Approach for the Multichannel Rendezvous Problem

no code implementations2 Jul 2019 Jen-Hung Wang, Ping-En Lu, Cheng-Shang Chang, Duan-Shin Lee

For such a multichannel rendezvous problem, we are interested in finding the optimal policy to minimize the expected time-to-rendezvous (ETTR) among the class of {\em dynamic blind rendezvous policies}, i. e., at the $t^{th}$ time slot each user selects channel $i$ independently with probability $p_i(t)$, $i=1, 2, \ldots, N$.

reinforcement-learning

ETTR Bounds and Approximation Solutions of Blind Rendezvous Policies in Cognitive Radio Networks with Random Channel States

no code implementations25 Jun 2019 Cheng-Shang Chang, Duan-Shin Lee, Yu-Lun Lin, Jen-Hung Wang

We first consider two channel models: (i) the fast time-varying channel model (where the channel states are assumed to be independent and identically distributed in each time slot), and (ii) the slow time-varying channel model (where the channel states remain unchanged over time).

Information Theory Information Theory

K-sets+: a Linear-time Clustering Algorithm for Data Points with a Sparse Similarity Measure

no code implementations11 May 2017 Cheng-Shang Chang, Chia-Tai Chang, Duan-Shin Lee, Li-Heng Liou

We then extend the applicability of the K-sets+ algorithm from data points in a semi-metric space to data points that only have a symmetric similarity measure.

Stochastic Block Model

A Mathematical Theory for Clustering in Metric Spaces

no code implementations25 Sep 2015 Cheng-Shang Chang, Wanjiun Liao, Yu-Sheng Chen, Li-Heng Liou

Such a duality result leads to a dual K-sets algorithm for clustering a set of data points with a cohesion measure.

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