An Analysis on the Cultural Function of Films from the Perpective of the Commercialization of Chinese Films

In 2019, China released his first hard science fiction1 film by Hollywood standards, which is an important step for the exploration of the development of Chinese commercial films. Much of the literature on this film is devoted to the analysis of its visual effects or to comparing it to Nolan's Interstellar (Christopher Nolan, UK & USA, 2014). At the same time, most documents focus too much to the “science fiction” label of this film, separating it from non-sci-fi commercial films. For the Chinese film industry, which is still in the initial stage of development, linking this epoch-making film with the previous films on the road of Chinese film development is beneficial to the exploration of the future film development. The focus of this dissertation, after linking these films, is to explore the relationship between commercial films and culture, raising related questions, such as: what are the factors that affect the spread of films overseas, or how does the film affect the cultural self-confidence of the country he belongs to? The rules represented by these relationships may be one of the consideration methods for the exploration and prediction of future film development. On the basis of exploring the relationship between commercial factors and culture as the goal, the experience summary of the correct path, ways of avoiding making detours as well, in the development of the Chinese film industry may be a reference for other countries or film groups in the world

Wasserstein Differential Privacy

Differential privacy (DP) has achieved remarkable results in the field of privacy-preserving machine learning. However, existing DP frameworks do not satisfy all the conditions for becoming metrics, which prevents them from deriving better basic private properties and leads to exaggerated values on privacy budgets. We propose Wasserstein differential privacy (WDP), an alternative DP framework to measure the risk of privacy leakage, which satisfies the properties of symmetry and triangle inequality. We show and prove that WDP has 13 excellent properties, which can be theoretical supports for the better performance of WDP than other DP frameworks. In addition, we derive a general privacy accounting method called Wasserstein accountant, which enables WDP to be applied in stochastic gradient descent (SGD) scenarios containing sub-sampling. Experiments on basic mechanisms, compositions and deep learning show that the privacy budgets obtained by Wasserstein accountant are relatively stable and less influenced by order. Moreover, the overestimation on privacy budgets can be effectively alleviated. The code is available at https://github.com/Hifipsysta/WDP.Comment: Accepted by AAAI 202

Existence of hyperbolic motions to a class of Hamiltonians and generalized NN-body system via a geometric approach

For the classical $N$-body problem in $\mathbb{R}^d$ with $d\ge2$, Maderna-Venturelli in their remarkable paper [Ann. Math. 2020] proved the existence of hyperbolic motions with any positive energy constant, starting from any configuration and along any non-collision configuration. Their original proof relies on the long time behavior of solutions by Chazy 1922 and Marchal-Saari 1976, on the H\"{o}lder estimate for Ma\~{n}\'{e}'s potential by Maderna 2012, and on the weak KAM theory. We give a new and completely different proof for the above existence of hyperbolic motions. The central idea is that, via some geometric observation, we build up uniform estimates for Euclidean length and angle of geodesics of Ma\~{n}\'{e}'s potential starting from a given configuration and ending at the ray along a given non-collision configuration. Note that we do not need any of the above previous studies used in Maderna-Venturelli's proof. Moreover, our geometric approach works for Hamiltonians $\frac12\|p\|^2-F(x)$, where $F(x)\ge 0$ is lower semicontinuous and decreases very slowly to $0$ faraway from collisions. We therefore obtain the existence of hyperbolic motions to such Hamiltonians with any positive energy constant, starting from any admissible configuration and along any non-collision configuration. Consequently, for several important potentials $F\in C^{2}(\Omega)$, we get similar existence of hyperbolic motions to the generalized $N$-body system $\ddot{x} = \nabla_x F(x)$, which is an extension of Maderna-Venturelli [Ann. Math. 2020].Comment: 37 pages, 6 figure

An Analysis of the Cause of Privacy Paradox among SNS Users: take Chinese College Students as an Example

It has been proved that the privacy paradox does exist, yet the cause of the phenomenon remains vague. This article tries to analyze the [Inserted: s]cause of privacy paradox phenomenon on SNS (WeChat) among Chinese college students based on Privacy Calculus Theory and the TPB model and introduces two new factors: the credibility of SNS and the cost of protecting privacy. Through a questionnaire and interview survey,[Inserted: a ] our result shows that there is no significant correlation between users’ privacy concerns and the intention of privacy disclosure. While the more users trust the SNS platform, the more possibility they tend to disclose their private information[Inserted: te], and the cost of privacy protection can somehow weaken the relationship between the intention and the actual behavior. Therefore, [Inserted: ship]by increasing SNS\u27s credibility, users tend to disclose more personal information to SNS providers, which may improve the competitiveness of SNSs and contribute to their sustainable development

Accelerated Federated Learning with Decoupled Adaptive Optimization

The federated learning (FL) framework enables edge clients to collaboratively learn a shared inference model while keeping privacy of training data on clients. Recently, many heuristics efforts have been made to generalize centralized adaptive optimization methods, such as SGDM, Adam, AdaGrad, etc., to federated settings for improving convergence and accuracy. However, there is still a paucity of theoretical principles on where to and how to design and utilize adaptive optimization methods in federated settings. This work aims to develop novel adaptive optimization methods for FL from the perspective of dynamics of ordinary differential equations (ODEs). First, an analytic framework is established to build a connection between federated optimization methods and decompositions of ODEs of corresponding centralized optimizers. Second, based on this analytic framework, a momentum decoupling adaptive optimization method, FedDA, is developed to fully utilize the global momentum on each local iteration and accelerate the training convergence. Last but not least, full batch gradients are utilized to mimic centralized optimization in the end of the training process to ensure the convergence and overcome the possible inconsistency caused by adaptive optimization methods

Photometric Metallicity Calibration with SDSS and SCUSS and its Application to distant stars in the South Galactic Cap

Based on SDSS g, r and SCUSS (South Galactic Cap of u-band Sky Survey) $u$ photometry, we develop a photometric calibration for estimating the stellar metallicity from $u-g$ and $g-r$ colors by using the SDSS spectra of 32,542 F- and G-type main sequence stars, which cover almost $3700$ deg$^{2}$ in the south Galactic cap. The rms scatter of the photometric metallicity residuals relative to spectrum-based metallicity is $0.14$ dex when $g-r<0.4$, and $0.16$ dex when $g-r>0.4$. Due to the deeper and more accurate magnitude of SCUSS $u$ band, the estimate can be used up to the faint magnitude of $g=21$. This application range of photometric metallicity calibration is wide enough so that it can be used to study metallicity distribution of distant stars. In this study, we select the Sagittarius (Sgr) stream and its neighboring field halo stars in south Galactic cap to study their metallicity distribution. We find that the Sgr stream at the cylindrical Galactocentric coordinate of $R\sim 19$ kpc, $\left| z\right| \sim 14$ kpc exhibits a relative rich metallicity distribution, and the neighboring field halo stars in our studied fields can be modeled by two-Gaussian model, with peaks respectively at [Fe/H]$=-1.9$ and [Fe/H]$=-1.5$.Comment: 8 pages, 7 figures, Accepted for publication in MNRA