Near-Optimal Algorithms for Differentially-Private Principal Components

Principal components analysis (PCA) is a standard tool for identifying good low-dimensional approximations to data in high dimension. Many data sets of interest contain private or sensitive information about individuals. Algorithms which operate on such data should be sensitive to the privacy risks in publishing their outputs. Differential privacy is a framework for developing tradeoffs between privacy and the utility of these outputs. In this paper we investigate the theory and empirical performance of differentially private approximations to PCA and propose a new method which explicitly optimizes the utility of the output. We show that the sample complexity of the proposed method differs from the existing procedure in the scaling with the data dimension, and that our method is nearly optimal in terms of this scaling. We furthermore illustrate our results, showing that on real data there is a large performance gap between the existing method and our method.Comment: 37 pages, 8 figures; final version to appear in the Journal of Machine Learning Research, preliminary version was at NIPS 201

Wavelet Thresholding for Image Noise Removal

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Low molecular weight heparin prophylaxis: a boon for women with history of placental mediated complications

Background: Prevention of placental mediated pregnancy complication is likely the best approach to decrease maternal mortality and morbidity. Anticoagulation therapy represents a good preventive option. Methods: A prospective randomized case control study was conducted at Safdarjang hospital. Patients were recruited from Sept. 2011 till May 2012 and followed till delivery. Thirty cases & controls were enrolled which comprised of non- thrombophilic patients with previous history of severe preeclampsia, Fetal Growth Restriction (FGR), severe placental abruption, stillbirth after 20 weeks. Study group received LMWH according to weight subcutaneously, once daily started at < 15 weeks till 36 weeks of gestation. Maternal outcomes were observed in both groups.Results: Incidence of stillbirth and abruption were significantly lower in study group (0 versus 3.3%, P = 0.05; and 0 versus 20%, P = 0.01). The respective incidence of severe preeclampsia and FGR were 6.6% versus 40% (P = 0.04) and 6.6% versus 30 % (P = 0.02). There was reduction of 72.7% of total adverse outcome.Conclusions: Prophylactic LMWH before 15 weeks of gestation decreases the incidence of placental mediated complications in non thrombophilic pregnant women who had previously suffered with these complications

REAL-TIME NETWORK EVENT CORRELATION BASED ON DEPENDENCY GRAPH FOR NETWORK ISSUE ROOT CAUSING

Techniques are described for a graph based approach to co-relate events in a network. The root cause of any network failure may be determined in real time