A5101675989- Sparse and Compressive Sensing Techniques
- Risk and Portfolio Optimization
- Financial Markets and Investment Strategies
- Face and Expression Recognition
- Photoacoustic and Ultrasonic Imaging
- Stochastic processes and financial applications
- Higher Education and Teaching Methods
- Blind Source Separation Techniques
- Numerical methods in inverse problems
- Advanced Image and Video Retrieval Techniques
- Neural Networks and Applications
- Medical Image Segmentation Techniques
- Industrial Vision Systems and Defect Detection
- Engineering Education and Curriculum Development
- Rough Sets and Fuzzy Logic
- Currency Recognition and Detection
- Optical Systems and Laser Technology
- Advanced Clustering Algorithms Research
- Blockchain Technology Applications and Security
- Adaptive optics and wavefront sensing
- Higher Education Learning Practices
- Computational and Text Analysis Methods
- Optical measurement and interference techniques
- Corporate Finance and Governance
- Digital Platforms and Economics
Xidian University
2021-2025
China University of Political Science and Law
2021-2024
Xi'an Jiaotong University
2005-2024
Central University of Finance and Economics
2024
Harbin Engineering University
2023
Henan Normal University
2012
Hebei University of Science and Technology
2010
Hangzhou Vocational and Technical College
2008
E-commerce has developed greatly in recent years, as such, its regulations have become one of the most important research areas order to implement a sustainable market. The analysis large amount reviews data generated shopping process can be used facilitate regulation: since review is short text and it easy extract features through deep learning methods. Through these features, sentiment carried out obtain users’ emotional tendency for specific product. Regulators formulate reasonable...
As a part of food safety research, researches on transactions has attracted increasing attention recently. Food choice is an important factor affecting safety: It can reflect consumer preferences and provide basis for market regulation. Therefore, this paper proposes regulation method based blockchain deep learning model: Stacked autoencoders (SAEs). Blockchain used to ensure the fairness achieve transparency within transaction process, thereby reducing complexity trading environment. In...
Enhanced-index-funds have attracted considerable attention from investors over the last decade, which aims at outperforming a benchmark index while maintaining similar risk level. In this article, we investigate an enhanced indexation methodology using Conditional Value-at-Risk (CVaR). particular, adopt CVaR of excess returns as measurement subject to cardinality constraint for controlling tracking portfolio scale precisely and tunable short-selling constraints adjusting margin each risky...
In this paper, we develop a robust conditional value at risk (CVaR) optimal portfolio rebalancing model under various financial constraints to construct sparse and diversified portfolios. Our includes transaction costs double cardinality in order capture the trade-off between limit of investment scale industry coverage requirement. We first derive closed-form solution for CVaR with only costs. This allows us conduct an analysis absence diversification constraints. Then, attempt remedy hidden...
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Multiview clustering, an unsupervised learning method, has gained significant attention. In this paper, we investigate a multiview clustering methodology using sparse optimization. A featured difference from the existing literatures is synergy of two types constraints. Specially, employ cardinality (also known as L0-norm) constraints to extract reliable structure information original data, and low-rank constraint reveal coherent within consensus affinity matrix. As result, propose novel...
Sparse portfolio optimization, which significantly boosts the out-of-sample performance of traditional mean-variance methods, is widely studied in fields optimization and financial economics. In this paper, we explore L1/L2 fractional regularization constructed by ratio L1 L2 norms on model to promote sparse selection. We present an regularized provide insights regarding short positions estimation errors. Then, develop efficient alternating direction method multipliers (ADMM) solve it...
In this paper, we develop a robust conditional value at risk (CVaR) optimal portfolio rebalancing model under various financial constraints to construct sparse and diversified portfolios. Our includes transaction costs double cardinality in order capture the trade-off between limit of investment scale industry coverage requirement. We first derive closed-form solution for CVaR with only costs. It allows us conduct analysis absence diversification constraints. Then, attempt remedy hidden by...
In this paper, we investigate an enhanced indexation methodology using robust Conditional Value-at-Risk (CVaR) and group-sparse optimization. A featured difference from the existing literatures is to describe tail risk worst-case CVaR of excess returns (WCVaR-ER), process industry selection a weighted $\ell_{\infty,1}$-norm constraint. We develop accelerated alternating minimization algorithm (AMA) for solving problem. At each iteration, method usually alternately solves convex cone program,...
In this paper, we investigate an enhanced indexation methodology using robust Conditional Value-at-Risk (CVaR) and group-sparse optimization. A featured difference from the existing literatures is to describe tail risk worst-case CVaR of excess returns (WCVaR-ER), process industry selection a weighted $\ell_{\infty,1}$-norm constraint. We develop accelerated alternating minimization algorithm (AMA) for solving problem. At each iteration, method usually alternately solves convex cone program,...
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