SCOPE: Scalable Composite Optimization for Learning on Spark

Many machine learning models, such as logistic regression~(LR) and support vector machine~(SVM), can be formulated as composite optimization problems. Recently, many distributed stochastic optimization~(DSO) methods have been proposed to solve the large-scale composite optimization problems, which have shown better performance than traditional batch methods. However, most of these DSO methods are not scalable enough. In this paper, we propose a novel DSO method, called \underline{s}calable \underline{c}omposite \underline{op}timization for l\underline{e}arning~({SCOPE}), and implement it on the fault-tolerant distributed platform \mbox{Spark}. SCOPE is both computation-efficient and communication-efficient. Theoretical analysis shows that SCOPE is convergent with linear convergence rate when the objective function is convex. Furthermore, empirical results on real datasets show that SCOPE can outperform other state-of-the-art distributed learning methods on Spark, including both batch learning methods and DSO methods

Algebraic Geometric Secret Sharing Schemes over Large Fields Are Asymptotically Threshold

In Chen-Cramer Crypto 2006 paper \cite{cc} algebraic geometric secret sharing schemes were proposed such that the "Fundamental Theorem in Information-Theoretically Secure Multiparty Computation" by Ben-Or, Goldwasser and Wigderson \cite{BGW88} and Chaum, Cr\'{e}peau and Damg{\aa}rd \cite{CCD88} can be established over constant-size base finite fields. These algebraic geometric secret sharing schemes defined by a curve of genus $g$ over a constant size finite field ${\bf F}_q$ is quasi-threshold in the following sense, any subset of $u \leq T-1$ players (non qualified) has no information of the secret and any subset of $u \geq T+2g$ players (qualified) can reconstruct the secret. It is natural to ask that how far from the threshold these quasi-threshold secret sharing schemes are? How many subsets of $u \in [T, T+2g-1]$ players can recover the secret or have no information of the secret? In this paper it is proved that almost all subsets of $u \in [T,T+g-1]$ players have no information of the secret and almost all subsets of $u \in [T+g,T+2g-1]$ players can reconstruct the secret when the size $q$ goes to the infinity and the genus satisfies $\lim \frac{g}{\sqrt{q}}=0$. Then algebraic geometric secret sharing schemes over large finite fields are asymptotically threshold in this case. We also analyze the case when the size $q$ of the base field is fixed and the genus goes to the infinity

Inhibition of TNF-α and IL-1 by compounds from selected plants for rheumatoid arthritis therapy: In vivo and in silico studies

Purpose: To investigate the inhibitory activities of herbal compounds from Curcuma longa, Sophora japonica and Camellia sinensis against tumor necrosis factor alpha (TNF-α) and interleukin-1 (IL-1) using in vivo and in silico tools.Methods: The extracts of the medicinal herbs (Curcuma longa, Sophora japonica and Camellia sinensis) were evaluated for immune-modulatory activities based using neutrophil oxidative burst assay. The compounds present in the medicinal herbs were screened for their inhibitory effects against TNF-α (PDB ID: 2AZ5) and IL-1 (PDB ID: 2L5X) using Molegro Virtual Docker 6.0 (MVD). The stabilities of the top docking poses were confirmed by Molecular Dynamics (MD) simulation run for 20 nanoseconds (ns).Results: The herbal compounds exerted strong inhibitory effects against TNF-α (PDB ID: 2AZ5) and IL- 1 (PDB ID: 2L5X), implying their therapeutic potential for use in rheumatoid arthritis (RA). Of the compounds, curcumin diglucoside and curcumin monoglucoside showed the strongest inhibitory effects on monocytes, with inhibitory levels of 82.75 and 81.34 %, respectively, while eugenin had the weakest inhibitory activity (11.12 %). In addition, molecular docking scores were consistent with the in vivo results, and revealed strong inhibitory effects of curcumin diglucoside and curcumin monoglucoside against TNF-α and IL-1.Conclusion: Herbal compounds present in Curcuma longa, Sophora japonica and Camellia sinensis possess strong inhibitory effects against the pro-inflammatory cytokines TNF-α and IL-1. Thus, these compounds have therapeutic potentials that can be exploited for the treatment of RA.Keywords: Curcuma longa, Sophora japonica, Camellia sinensis, Rheumatoid arthritis, Cytokines, TNF-α, IL-1, Immuno-modulation, Molecular dockin