Differentially Private Learning with Per-Sample Adaptive Clipping

Privacy in AI remains a topic that draws attention from researchers and the general public in recent years. As one way to implement privacy-preserving AI, differentially private learning is a framework that enables AI models to use differential privacy (DP). To achieve DP in the learning process, existing algorithms typically limit the magnitude of gradients with a constant clipping, which requires carefully tuned due to its significant impact on model performance. As a solution to this issue, latest works NSGD and Auto-S innovatively propose to use normalization instead of clipping to avoid hyperparameter tuning. However, normalization-based approaches like NSGD and Auto-S rely on a monotonic weight function, which imposes excessive weight on small gradient samples and introduces extra deviation to the update. In this paper, we propose a Differentially Private Per-Sample Adaptive Clipping (DP-PSAC) algorithm based on a non-monotonic adaptive weight function, which guarantees privacy without the typical hyperparameter tuning process of using a constant clipping while significantly reducing the deviation between the update and true batch-averaged gradient. We provide a rigorous theoretical convergence analysis and show that with convergence rate at the same order, the proposed algorithm achieves a lower non-vanishing bound, which is maintained over training iterations, compared with NSGD/Auto-S. In addition, through extensive experimental evaluation, we show that DP-PSAC outperforms or matches the state-of-the-art methods on multiple main-stream vision and language tasks.Comment: To appear in AAAI 2023, Revised acknowledgments and citation

The two-loop contributions to muon MDM in U(1)XU(1)_X SSM

The MSSM is extended to the $U(1)_X$SSM, whose local gauge group is $SU(3)_C \times SU(2)_L \times U(1)_Y \times U(1)_X$. To obtain the $U(1)_X$SSM, we add the new superfields to the MSSM, namely: three Higgs singlets $\hat{\eta},~\hat{\bar{\eta}},~\hat{S}$ and right-handed neutrinos $\hat{\nu}_i$. It can give light neutrino tiny mass at the tree level through the seesaw mechanism. The study of the contribution of the two-loop diagrams to the MDM of muon under $U(1)_X$SSM provides the possibility for us to search for new physics. In the analytical calculation of the loop diagrams (one-loop and two-loop diagrams), the effective Lagrangian method is used to derive muon MDM. Here, the considered two-loop diagrams include Barr-Zee type diagrams and rainbow type two-loop diagrams, especially Z-Z rainbow two-loop diagram is taken into account. The obtained numerical results can reach $7.4\times10^{-10}$, which can remedy the deviation between SM prediction and experimental data to some extent.Comment: 19 pages, 8 figure

Nonlinear behavior of the Chinese SSEC index with a unit root: Evidence from threshold unit root tests

We investigate the behavior of the Shanghai Stock Exchange Composite (SSEC) index for the period from 1990:12 to 2007:06 using an unconstrained two-regime threshold autoregressive (TAR) model with an unit root developed by Caner and Hansen. The method allows us to simultaneously consider non-stationarity and nonlinearity in financial time series. Our finding indicates that the Shanghai stock market exhibits nonlinear behavior with two regimes and has unit roots in both regimes. The important implications of the threshold effect in stock markets are also discussed.Comment: 10 Elsart pages + 5 tables + 1 eps figur

Changes in the proteomic profiles of mouse brain after infection with cyst-forming Toxoplasma gondii

Background Toxoplasma gondii is an opportunistic pathogenic protozoan parasite, which infects approximately one third of the human population worldwide, causing opportunistic zoonotic toxoplasmosis. The predilection of T. gondii for the central nervous system (CNS) causes behavioral disorders and fatal necrotizing encephalitis and thus constitutes a major threat especially to AIDS patients. Methods In the present study, we explored the proteomic profiles of brain tissues of the specific pathogen-free (SPF) Kunming mice at 7 d, 14 d and 21 d after infection with cysts of the Toxoplasma gondii Prugniaud (PRU) strain (Genotype II), by two-dimensional gel electrophoresis (2-DE) combined with MALDI-TOF/TOF tandem mass spectrometry (MS/MS). Results A total of 60 differentially expressed protein spots were selected. Fifty-six spots were successfully identified, which corresponded to 45 proteins of the mouse. Functional analysis using a Gene Ontology database showed that these proteins were mainly involved in metabolism, cell structure, signal transduction and immune responses, and will be beneficial for the understanding of molecular mechanisms of T. gondii pathogenesis. Conclusions This study identified some mouse brain proteins involved in the response with cyst-forming T. gondii PRU strain. These results provided an insight into the responsive relationship between T. gondii and the host brain tissues, which will shed light on our understanding of the mechanisms of pathogenesis in toxoplasmic encephalitis, and facilitate the discovery of new methods of diagnosis, prevention, control and treatment of toxoplasmic encephalopathy

Predictive value of alpha-fetoprotein in the long-term risk of developing hepatocellular carcinoma in patients with hepatitis B virus infection--results from a clinic-based longitudinal cohort.

BACKGROUND: Although serum level of alpha-fetoprotein (AFP) has long been used to complement imaging tests in the screening and diagnosis of hepatocellular carcinoma (HCC), whether it can be used as a predictive marker of long-term risk for developing HCC in patients with hepatitis B virus (HBV) has not been extensively evaluated and thus remains controversial. METHODS: We retrospectively conducted a clinic-based longitudinal cohort study including 617 Korean American patients with HBV who had been followed for up to 22 years (median follow-up time, 6.2 years) to evaluate the association between baseline serum AFP level and the long-term risk of HCC. RESULTS: The median baseline AFP value of these patients was 3.8 ng/ml. Compared to patients with lower-than-median AFP value, those with higher-than-median baseline serum AFP had a significantly increased risk of developing HCC with a hazard ratio (HR) of 2.73 (95% confidence interval [CI] 1.25-5.99), independent of other major HCC risk factors. In addition, we calculated the cumulative incidence of HCC during different years of follow-up time by baseline serum AFP, and found that the cumulative incidence of HCC was significantly higher in HBV patients with high baseline serum AFP compared to those with low baseline serum AFP in each of the five follow-up time periods examined. CONCLUSIONS: Our results indicated that AFP was a strong independent prospective predictor of long-term HCC risk in high-risk HBV patients. More targeted prevention and early detection of HCC may be considered for these patients

DNetDB: The human disease network database based on dysfunctional regulation mechanism

Additional analysis and concepts explanation. This file contains 1) comparison of DNetDB and the results of differential expression analysis (DEA-) based method ; 2) comparison of DNetDB and traditional disease classification; 3) negative disease relationships and 4) DCp and DCe. (DOCX 6926 kb