Renmin University of China

About: Renmin University of China is a education organization based out in Beijing, Beijing, China. It is known for research contribution in the topics: China & Population. The organization has 11325 authors who have published 15498 publications receiving 238419 citations. The organization is also known as: Renmin University & People's University of China.

Self-supervised Learning: Generative or Contrastive.

Abstract: Deep supervised learning has achieved great success in the last decade. However, its deficiencies of dependence on manual labels and vulnerability to attacks have driven people to explore a better solution. As an alternative, self-supervised learning attracts many researchers for its soaring performance on representation learning in the last several years. Self-supervised representation learning leverages input data itself as supervision and benefits almost all types of downstream tasks. In this survey, we take a look into new self-supervised learning methods for representation in computer vision, natural language processing, and graph learning. We comprehensively review the existing empirical methods and summarize them into three main categories according to their objectives: generative, contrastive, and generative-contrastive (adversarial). We further investigate related theoretical analysis work to provide deeper thoughts on how self-supervised learning works. Finally, we briefly discuss open problems and future directions for self-supervised learning. An outline slide for the survey is provided.

Comprehensive Investigation on the Thermal Stability of 66 Ionic Liquids by Thermogravimetric Analysis

Abstract: The thermal stabilities of 66 ionic liquids (ILs) were investigated using the thermogravimetric analysis (TGA) method. Isothermal TGA studies on the ILs showed that ILs exhibit decomposition at temperatures lower than the onset decomposition temperature (Tonset), which is determined from ramped temperature TGA experiments. Thermal decomposition kinetics of ILs was analyzed using pseudo-zero-order rate expression and their activation energy was obtained. Parameter T0.01/10h, the temperature at which 1% mass loss occurs in 10 h, was used to evaluate the long-term thermal stability of ILs. The thermal stability of the ILs was classified to five levels according to Tonset. The ILs thermal stability is dependent on the structure of ILs, i.e., cation modification, cation and anion type. The correlations between the stability and the hydrophilicity of ILs were discussed. Finally, the thermal stabilities of acetate-based ILs, amino acid ILs, and dicyanamide ILs were analyzed.

The urban–rural income gap and inequality in china

Abstract: Using new household survey data for 1995 and 2002, we investigate the size of China's urban–rural income gap, the gap's contribution to overall inequality in China, and the factors underlying the gap. Our analysis improves on past estimates by using a fuller measure of income, adjusting for spatial price differences and including migrants. Our methods include inequality decomposition by population subgroup and the Oaxaca–Blinder decomposition. Several key findings emerge. First, the adjustments substantially reduce China's urban–rural income gap and its contribution to inequality. Nevertheless, the gap remains large and has increased somewhat over time. Second, after controlling for household characteristics, location of residence remains the most important factor underlying the urban–rural income gap. The only household characteristic that contributes substantially to the gap is education. Differences in the endowments of, and returns to, other household characteristics such as family size and composition, landholdings, and Communist Party membership are relatively unimportant.

Identification of overlapping community structure in complex networks using fuzzy c-means clustering

Abstract: Identification of (overlapping) communities/clusters in a complex network is a general problem in data mining of network data sets. In this paper, we devise a novel algorithm to identify overlapping communities in complex networks by the combination of a new modularity function based on generalizing NG's Q function, an approximation mapping of network nodes into Euclidean space and fuzzy c-means clustering. Experimental results indicate that the new algorithm is efficient at detecting both good clusterings and the appropriate number of clusters.