What Can We Learn Privately?

Learning problems form an important category of computational tasks that generalizes many of the computations researchers apply to large real-life data sets. We ask: what concept classes can be learned privately, namely, by an algorithm whose output does not depend too heavily on any one input or specific training example? More precisely, we investigate learning algorithms that satisfy differential privacy, a notion that provides strong confidentiality guarantees in contexts where aggregate information is released about a database containing sensitive information about individuals. We demonstrate that, ignoring computational constraints, it is possible to privately agnostically learn any concept class using a sample size approximately logarithmic in the cardinality of the concept class. Therefore, almost anything learnable is learnable privately: specifically, if a concept class is learnable by a (non-private) algorithm with polynomial sample complexity and output size, then it can be learned privately using a polynomial number of samples. We also present a computationally efficient private PAC learner for the class of parity functions. Local (or randomized response) algorithms are a practical class of private algorithms that have received extensive investigation. We provide a precise characterization of local private learning algorithms. We show that a concept class is learnable by a local algorithm if and only if it is learnable in the statistical query (SQ) model. Finally, we present a separation between the power of interactive and noninteractive local learning algorithms.Comment: 35 pages, 2 figure

Stress-strain properties of ferritic steels using automated ball-indentation testing - pile-up effects included

The automated Ball-Indentation (Bl) testing is based cm repeated indentation of a spherical indenter at a single location on a metallic sample. The indentation loads and the corresponding depths in an indentation are used to extract the key mechanical flow properties using well established mathematical relationships. The technique is almost nondestructive and an excellent substitute for the conventional tensile test especially when there is very little volume of specimen available for testing. The distortion at the original plane of surface caused by the material displaced by the indentation is referred to as the pile-up or sink-in effect. The pile-up behaviour alters the actual contact area and hence the indentation diameter which is used for calculating tire stress-strain parameters. It is well established that the extent of pile-up is related to the strain hardening coefficient of the material. This paper describes the methodology for deriving the plastic stress-strain properties by automated ball-indentation technique taking into account the usually ignored pile-up effects. Flow properties derived from ball-indentation tests using die proposed methodology were found to be in good agreement with those of tensile test results for various ferritic steels like AISI 1025 carbon steel, 2.25C:r-lMo steel, Mod 9Cr-lMo steel with different work hardening characteristics

Meeting the challenges related to material issues in chemical industries

Reliable performance and profitability are two important requirements for any chemical industry. In order to achieve high level of reliability and excellent performance, several issues related to design, materials selection, fabrication, quality assurance, transport, storage, inputs from condition monitoring, failure analysis etc. have to be adequately addressed and implemented. Technology related to nondestructive testing and monitoring of the plant is also essential for precise identification of defect sites and to take appropriate remedial decision regarding repair, replacement or modification of process conditions. The interdisciplinary holistic approach enhances the life of critical engineering components in chemical plants. Further, understanding the failure modes of the components through the analysis of failed components throws light on the choice of appropriate preventive measures to be taken well in advance, to have a control over the overall health of the plant. The failure analysis also leads to better design modification and condition monitoring methodologies, for the next generation components and plants. At the Indira Gandhi Centre for Atomic Research (IGCAR), Kalpakkam, a unique combination of the expertise in design, materials selection, fabrication, NDT development, condition monitoring, life prediction and failure analysis exists to obtain desired results for achieving high levels of reliability and performance assessment of critical engineering components in chemical industries. Case studies related to design, materials selection and fabrication aspects of critical components in nuclear fuel reprocessing plants, NDT development and condition monitoring of various components of nuclear power plants, and important failure investigations on critical engineering components in chemical and allied industries are discussed in this paper. Future directions are identified and planned approaches are briefly described

Neuroprotective effect of secretin in chronic hypoxia induced neurodegeneration in rats

Background: Hypoxia is a condition in any stage in the delivery of oxygen to cells which include decreased partial pressures of oxygen, less diffusion of oxygen in the lungs, insufficient hemoglobin, inefficient blood flow to the end tissue, and breathing rhythm. Secretin is an amino acid which plays proper functioning of gastro intestinal system.Methods: The current study was conducted to evaluvate the effect of exogenously administrated secretin on chronic hypoxic damage of brain in rat model. Experimental design consists of control animals, Control animals + secretin hypoxia exposed animals; hypoxia exposed animals +secretin (20ng/kg.bw).Results: The results of this study point to a possible role of Secretin as neuroprotectant.Conclusions: Further research on secretin needs to be conducted in order to confirm the deductions made by this study

Private Incremental Regression

Data is continuously generated by modern data sources, and a recent challenge in machine learning has been to develop techniques that perform well in an incremental (streaming) setting. In this paper, we investigate the problem of private machine learning, where as common in practice, the data is not given at once, but rather arrives incrementally over time. We introduce the problems of private incremental ERM and private incremental regression where the general goal is to always maintain a good empirical risk minimizer for the history observed under differential privacy. Our first contribution is a generic transformation of private batch ERM mechanisms into private incremental ERM mechanisms, based on a simple idea of invoking the private batch ERM procedure at some regular time intervals. We take this construction as a baseline for comparison. We then provide two mechanisms for the private incremental regression problem. Our first mechanism is based on privately constructing a noisy incremental gradient function, which is then used in a modified projected gradient procedure at every timestep. This mechanism has an excess empirical risk of $\approx\sqrt{d}$, where $d$ is the dimensionality of the data. While from the results of [Bassily et al. 2014] this bound is tight in the worst-case, we show that certain geometric properties of the input and constraint set can be used to derive significantly better results for certain interesting regression problems.Comment: To appear in PODS 201

Development and application of C - scan ultrasonic facility

This paper presents the in-house development and application of a C-scan ultrasonic facility ULTIMA 200M2 at the Indira Gandhi Centre for Atomic Research (IGCAR), Kalpakkam, carried out in collaboration with the Electronics Division, Bhabha Atomic Research Centre (BARC), Mumbai. The paper describes various constituents of the system developed and also highlights the typical results obtained using this system, including bond integrity assessment of explosive welds and imaging of fuel sub-assembly heads of the Fast Breeder Test Reactor. The system has also been used for imaging both the sides of a one rupee Indian coin. All the finer details of the coin could be extracted, demonstrating the resolution capabilities of the system

In-orbit Performance of UVIT on ASTROSAT

We present the in-orbit performance and the first results from the ultra-violet Imaging telescope (UVIT) on ASTROSAT. UVIT consists of two identical 38cm coaligned telescopes, one for the FUV channel (130-180nm) and the other for the NUV (200-300nm) and VIS (320-550nm) channels, with a field of view of 28 $arcmin$. The FUV and the NUV detectors are operated in the high gain photon counting mode whereas the VIS detector is operated in the low gain integration mode. The FUV and NUV channels have filters and gratings, whereas the VIS channel has filters. The ASTROSAT was launched on 28th September 2015. The performance verification of UVIT was carried out after the opening of the UVIT doors on 30th November 2015, till the end of March 2016 within the allotted time of 50 days for calibration. All the on-board systems were found to be working satisfactorily. During the PV phase, the UVIT observed several calibration sources to characterise the instrument and a few objects to demonstrate the capability of the UVIT. The resolution of the UVIT was found to be about 1.4 - 1.7 $arcsec$ in the FUV and NUV. The sensitivity in various filters were calibrated using standard stars (white dwarfs), to estimate the zero-point magnitudes as well as the flux conversion factor. The gratings were also calibrated to estimate their resolution as well as effective area. The sensitivity of the filters were found to be reduced up to 15\% with respect to the ground calibrations. The sensitivity variation is monitored on a monthly basis. UVIT is all set to roll out science results with its imaging capability with good resolution and large field of view, capability to sample the UV spectral region using different filters and capability to perform variability studies in the UV.Comment: 10 pages, To appear in SPIE conference proceedings, SPIE conference paper, 201

The number of matchings in random graphs

We study matchings on sparse random graphs by means of the cavity method. We first show how the method reproduces several known results about maximum and perfect matchings in regular and Erdos-Renyi random graphs. Our main new result is the computation of the entropy, i.e. the leading order of the logarithm of the number of solutions, of matchings with a given size. We derive both an algorithm to compute this entropy for an arbitrary graph with a girth that diverges in the large size limit, and an analytic result for the entropy in regular and Erdos-Renyi random graph ensembles.Comment: 17 pages, 6 figures, to be published in Journal of Statistical Mechanic

Identification of ORC1/CDC6-Interacting Factors in Trypanosoma brucei Reveals Critical Features of Origin Recognition Complex Architecture

DNA Replication initiates by formation of a pre-replication complex on sequences termed origins. In eukaryotes, the pre-replication complex is composed of the Origin Recognition Complex (ORC), Cdc6 and the MCM replicative helicase in conjunction with Cdt1. Eukaryotic ORC is considered to be composed of six subunits, named Orc1–6, and monomeric Cdc6 is closely related in sequence to Orc1. However, ORC has been little explored in protists, and only a single ORC protein, related to both Orc1 and Cdc6, has been shown to act in DNA replication in Trypanosoma brucei. Here we identify three highly diverged putative T. brucei ORC components that interact with ORC1/CDC6 and contribute to cell division. Two of these factors are so diverged that we cannot determine if they are eukaryotic ORC subunit orthologues, or are parasite-specific replication factors. The other we show to be a highly diverged Orc4 orthologue, demonstrating that this is one of the most widely conserved ORC subunits in protists and revealing it to be a key element of eukaryotic ORC architecture. Additionally, we have examined interactions amongst the T. brucei MCM subunits and show that this has the conventional eukaryotic heterohexameric structure, suggesting that divergence in the T. brucei replication machinery is limited to the earliest steps in origin licensing