7 citations · 17 across the 14 of their papers we have counts for
14 papers
Perceptual Indistinguishability-Net (PI-Net): Facial Image Obfuscation with Manipulable Semantics
Jia-Wei Chen, Li-Ju Chen, Chia-Mu Yu +1
With the growing use of camera devices, the industry has many image datasets that provide more opportunities for collaboration between the machine learning community and industry.…
Deterministic Certification to Adversarial Attacks via Bernstein Polynomial Approximation
Ching-Chia Kao, Jhe-Bang Ko, Chun-Shien Lu
Randomized smoothing has established state-of-the-art provable robustness against norm adversarial attacks with high probability. However, the introduced Gaussian data aug…
Greedy Algorithms for Hybrid Compressed Sensing
Ching-Lun Tai, Sung-Hsien Hsieh, Chun-Shien Lu
Compressed sensing (CS) is a technique which uses fewer measurements than dictated by the Nyquist sampling theorem. The traditional CS with linear measurements achieves efficient r…
Link Delay Estimation Using Sparse Recovery for Dynamic Network Tomography
Hao-Ting Wei, Sung-Hsien Hsieh, Wen-Liang Hwang +2
When the scale of communication networks has been growing rapidly in the past decades, it becomes a critical challenge to extract fast and accurate estimation of key state paramete…
Distributed Compressive Sensing: Performance Analysis with Diverse Signal Ensembles
Sung-Hsien Hsieh, Wei-Jie Liang, Chun-Shien Lu +1
Distributed compressive sensing is a framework considering jointly sparsity within signal ensembles along with multiple measurement vectors (MMVs). The current theoretical bound of…
Fast Binary Embedding via Circulant Downsampled Matrix -- A Data-Independent Approach
Sung-Hsien Hsieh, Chun-Shien Lu, Soo-Chang Pei
Binary embedding of high-dimensional data aims to produce low-dimensional binary codes while preserving discriminative power. State-of-the-art methods often suffer from high comput…
Performance Analysis of Joint-Sparse Recovery from Multiple Measurements and Prior Information via Convex Optimization
Shih-Wei Hu, Gang-Xuan Lin, Sung-Hsien Hsieh +2
We address the problem of compressed sensing with multiple measurement vectors associated with prior information in order to better reconstruct an original sparse matrix signal. $\…
Fast Template Matching by Subsampled Circulant Matrix
Sung-Hsien Hsieh, Chun-Shien Lu, and Soo-Chang Pei
Template matching is widely used for many applications in image and signal processing and usually is time-critical. Traditional methods usually focus on how to reduce the search lo…
Fast Greedy Approaches for Compressive Sensing of Large-Scale Signals
Sung-Hsien Hsieh, Chun-Shien Lu, Soo-Chang Pei
Cost-efficient compressive sensing is challenging when facing large-scale data, {\em i.e.}, data with large sizes. Conventional compressive sensing methods for large-scale data wil…
Compressive Sensing of Large-Scale Images: An Assumption-Free Approach
Wei-Jie Liang, Gang-Xuan Lin, Chun-Shien Lu
Cost-efficient compressive sensing of big media data with fast reconstructed high-quality results is very challenging. In this paper, we propose a new large-scale image compressive…
The Necessary And Sufficient Condition for Generalized Demixing
Chun-Yen Kuo, Gang-Xuan Lin, Chun-Shien Lu
Demixing is the problem of identifying multiple structured signals from a superimposed observation. This work analyzes a general framework, based on convex optimization, for solvin…
Sparse Fast Fourier Transform for Exactly and Generally K-Sparse Signals by Downsampling and Sparse Recovery
Sung-Hsien Hsieh, Chun-Shien Lu, Soo-Chang Pei
Fast Fourier Transform (FFT) is one of the most important tools in digital signal processing. FFT costs O(N \log N) for transforming a signal of length N. Recently, Sparse Fourier…
Secure Multidimensional Queries in Tiered Sensor Networks
Chia-Mu Yu, Chun-Shien Lu, Sy-Yen Kuo
In this paper, aiming at securing range query, top-k query, and skyline query in tiered sensor networks, we propose the Secure Range Query (SRQ), Secure Top- Query (STQ), and Se…
Constrained Function Based En-Route Filtering for Sensor Networks
Chia-Mu Yu, Chun-Shien Lu, Sy-Yen Kuo
Sensor networks are vulnerable to \emph{false data injection attack} and \emph{path-based DoS} (PDoS) attack. While conventional authentication schemes are insufficient for solving…