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- The University of SydneyAU198 papers
- Centre for Quantum Computation and Communication TechnologyAU120 papers
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- Commonwealth Scientific and Industrial Research OrganisationAU75 papers
- Chinese Academy of SciencesCN74 papers
- Macquarie UniversityAU68 papers
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- Data61AU43 papers
- ARC Centre of Excellence for Transformative Meta-Optical SystemsAU41 papers
- Nanyang Technological UniversitySG41 papers
62 papers · 1 filter
Spectrum and Energy Efficiency Evaluation of Two-Tier Femtocell networks With Partially Open Channels
Xiaohu Ge, Tao Han, Yan Zhang +5
Two-tier femtocell networks is an efficient communication architecture that significantly improves throughput in indoor environments with low power consumption. Traditionally, a fe…
Optimizing Photovoltaic Charge Generation of Nanowire Arrays: A Simple Semi-Analytic Approach
Björn C. P. Sturmberg, Kokou B. Dossou, Lindsay C. Botten +4
Nanowire arrays exhibit efficient light coupling and strong light trapping, making them well suited to solar cell applications. The processes that contribute to their absorption ar…
Multi-scale quantum simulation of quantum field theory using wavelets
Gavin K. Brennen, Peter Rohde, Barry C. Sanders +1
A successful approach to understand field theories is to resolve the physics into different length or energy scales using the renormalization group framework. We propose a quantum…
The Private and Public Correlation Cost of Three Random Variables with Collaboration
Eric Chitambar, Min-Hsiu Hsieh, Andreas Winter
In this paper we consider the problem of generating arbitrary three-party correlations from a combination of public and secret correlations. Two parties -- called Alice and Bob --…
A Convex Formulation for Spectral Shrunk Clustering
Xiaojun Chang, Feiping Nie, Zhigang Ma +2
Spectral clustering is a fundamental technique in the field of data mining and information processing. Most existing spectral clustering algorithms integrate dimensionality reducti…
A Convex Sparse PCA for Feature Analysis
Xiaojun Chang, Feiping Nie, Yi Yang +1
Principal component analysis (PCA) has been widely applied to dimensionality reduction and data pre-processing for different applications in engineering, biology and social science…