SAAGs: Biased stochastic variance reduction methods for large-scale learning

Stochastic approximation is one of the effective approach to deal with the large-scale machine learning problems and the recent research has focused on reduction of variance, caused by the noisy approximations of the gradients. In this paper, we have proposed novel variants of SAAG-I and II (Stochastic Average Adjusted Gradient) (Chauhan et al. 2017), called SAAG-III and IV, respectively. Unlike SAAG-I, starting point is set to average of previous epoch in SAAG-III, and unlike SAAG-II, the snap point and starting point are set to average and last iterate of previous epoch in SAAG-IV, respectively. To determine the step size, we have used Stochastic Backtracking-Armijo line Search (SBAS) which performs line search only on selected mini-batch of data points. Since backtracking line search is not suitable for large-scale problems and the constants used to find the step size, like Lipschitz constant, are not always available so SBAS could be very effective in such cases. We have extended SAAGs (I, II, III and IV) to solve non-smooth problems and designed two update rules for smooth and non-smooth problems. Moreover, our theoretical results have proved linear convergence of SAAG-IV for all the four combinations of smoothness and strong-convexity, in expectation. Finally, our experimental studies have proved the efficacy of proposed methods against the state-of-art techniques

Faster learning by reduction of data access time

Nowadays, the major challenge in machine learning is the Big Data challenge. The big data problems due to large number of data points or large number of features in each data point, or both, the training of models have become very slow. The training time has two major components: Time to access the data and time to process (learn from) the data. So far, the research has focused only on the second part, i.e., learning from the data. In this paper, we have proposed one possible solution to handle the big data problems in machine learning. The idea is to reduce the training time through reducing data access time by proposing systematic sampling and cyclic/sequential sampling to select mini-batches from the dataset. To prove the effectiveness of proposed sampling techniques, we have used Empirical Risk Minimization, which is commonly used machine learning problem, for strongly convex and smooth case. The problem has been solved using SAG, SAGA, SVRG, SAAG-II and MBSGD (Mini-batched SGD), each using two step determination techniques, namely, constant step size and backtracking line search method. Theoretical results prove the same convergence for systematic sampling, cyclic sampling and the widely used random sampling technique, in expectation. Experimental results with bench marked datasets prove the efficacy of the proposed sampling techniques and show up to six times faster training

Foliar sprays of concentrated urea at maturity of pigeonpea to induce defoliation and increase its residual benefit to wheat

The pigeonpea (Cajanus cajan (L.) Millsp.) crop retains appreciable amounts of green foliage even after reaching physiological maturity, which if allowed to defoliate, could augment the residual benefit of pigeonpea to the following wheat (Triticum aestivum L.) in a pigeonpea–wheat rotation. The effect of addition of leaves present on mature pigeonpea crop to the soil was examined on the following wheat during the 1999/2000 growing season at Patancheru (17840N, 78820E) and during the 2001–2003 growing seasons at Modipuram (29840N, 77880E). At Patancheru, an extra-short-duration pigeonpea cultivar ICPL 88039 was defoliated manually and using foliar sprays of 10% urea (30 kg/ha) and compared with a millet (Pennisetum glaucum (L.) R.Br.) crop, naturally senesced leaf residue and no-leaf residue controls. At Modipuram, the effect of 10% urea spray treatment on mature ICPL 88039 was compared with the unsprayed control. At both locations, the rainy season crops were followed by a wheat cultivar UP 2338 at four nitrogen levels applied in a split plot design, which at Patancheru were 0, 30, 90 and 120 kg N ha 1 and at Modipuram 0, 60, 120 and 180 kg N ha 1. At Patancheru, urea spray added 0.5 t ha 1 of extra leaf litter to the soil within a week without significantly affecting pigeonpea yield. This treatment, however, increased mean wheat yield by 29% from 2.4 t ha 1 in the no-leaf residue pigeonpea or pearl millet plots to 3.1 t ha 1. At Modipuram, the foliar sprays of urea added more leaf litter to the soil than at Patancheru. Here, increase in subsequent wheat yield due to additional pigeonpea leaf litter was 7–8% and net profit 21% more than in the unsprayed control. The addition of pigeonpea leaf litter to the soil resulted in a saving of 40–60 kg N for the following wheat crops in both the environments. The results demonstrated that pigeonpea leaf litter could play an important role in the fertilizer N economy in wheat. The urea spray at maturity of the standing pigeonpea crop significantly improved this contribution in increasing wheat yield, the effect of which was additional to the amount of urea used for inducing defoliation. The practice, if adopted by farmers, may enhance sustainability of wheat production system in an environmentally friendly way, as it could reduce the amount of fertilizer N application to soil and enhance wheat yield

Diversification of rice with pigeonpea in a rice-wheat cropping system on a Typic Ustochrept: effect on soil fertility, yield and nutrient use efficiency

Continuous adoption of rice-wheat cropping system (RWCS) has led to depletion of inherent soil fertility resulting in a serious threat to its sustainability in the Indo-Gangetic plain region (IGPR) of India. The inclusion of legumes in RWCS assumes a great significance to restore soil fertility. But farmers in the IGPR rarely grow legumes in the system. We, therefore, carried out farmers' participatory diagnostic survey in the Upper Gangetic plain zone (UGP) to understand farmers' fertilizer management practices for wheat (Trititicum aestivum L. Emend Fiori & Paol) following rice (Oryza sativa L.) or pigeonpea (Cajanus cajan (L.) Millsp). The survey indicated that most of the farmers in UGP grew pigeonpea in place of rice under RWCS as only a break crop at a 2-3 year interval. The farmers applied, on average, 11 kg N ha-1 and 24 kg P ha-1 to wheat sown after rice, and 12 kg N ha-1 and 19 kg P ha-1 to wheat sown after pigeonpea. Wheat yields, however, were lower (3.3 t ha-1) when sown after pigeonpea than after rice (3.7 t ha-1). The survey was followed by a field experiment at Modipuram (29°4′N), Meerut, India that continued during the three consecutive years (1998-1999 to 2000-2001) to examine the effect of inclusion of pigeonpea in place of rice on soil fertility, N and P use efficiency and yields of wheat. In 1998-1999, wheat yields after pigeonpea were lower than after rice, but improved significantly (p<0.05) by 11.4-15.1% in pigeonpea plots compared with those in rice plots during 1999-2000 and 2000-2001, respectively. The use efficiency of applied N and P fertilizers in wheat, measured as agronomic efficiency and apparent recovery, was increased with combined use of fertilizer N and P at recommended rate, and also with inclusion of pigeonpea in place of rice. The post-wheat harvest NO3-N in soil profile beyond 45 cm depth was significantly greater under rice-wheat system than under pigeonpea-wheat system, suggesting that inclusion of pigeonpea may help in minimizing NO3-N leaching to deeper profile layers beyond root zone. Similarly, in the treatments receiving both 120 kg N and 26 kg P ha-1, NO3-N beyond 45 cm soil depth was lower compared to those receiving N or P alone. Inclusion of pigeonpea in place of rice enhanced carbon accumulation in the soil profile. The available P content was, however, invariably low under pigeonpea plots as compared to that under rice. With continuous rice-wheat cropping, the bulk density (BD) of soil was increased, especially in the 30-45 cm soil profile. Inclusion of pigeonpea in the system not only helped maintaining soil BD at initial level in the surface (0-15 cm) soil layers, but also in decreasing (p<0.05) BD in sub-surface layers (15-30 cm and 30-45 cm). Compared to rice, a statistically significant (p<0.05) positive effect of pigeonpea on root volume (58%) and root weight (99.5%) of succeeding wheat was also recorded. The net economic returns under pigeonpea-wheat system were greater compared with rice-wheat syste

Large vessel vasculitis

Takayasu arteritis is a chronic granulomatous disease of the aorta and its major branches that usually affects women during the second and third decades of life, but it has been reported in young children. This review details the clinical, pathological and radiological features, differential diagnoses and management of the condition, focusing chiefly on the disease in children. The recent definition of Takayasu arteritis is discussed. The condition should be considered in patients with unexplained arterial hypertension or unexplained inflammatory syndromes without signs of localization. Since the disease may be life-threatening and progressive, early recognition is necessary to initiate appropriate therapy. Patients with persistent ischaemic symptoms including hypertension might benefit from revascularization procedures

Infant and Child Mortality in India in the Last Two Decades: A Geospatial Analysis

Studies examining the intricate interplay between poverty, female literacy, child malnutrition, and child mortality are rare in demographic literature. Given the recent focus on Millennium Development Goals 4 (child survival) and 5 (maternal health), we explored whether the geographic regions that were underprivileged in terms of wealth, female literacy, child nutrition, or safe delivery were also grappling with the elevated risk of child mortality; whether there were any spatial outliers; whether these relationships have undergone any significant change over historical time periods.The present paper attempted to investigate these critical questions using data from household surveys like NFHS 1992-1993, NFHS 1998-1999 and DLHS 2002-2004. For the first time, we employed geo-spatial techniques like Moran's-I, univariate LISA, bivariate LISA, spatial error regression, and spatiotemporal regression to address the research problem. For carrying out the geospatial analysis, we classified India into 76 natural regions based on the agro-climatic scheme proposed by Bhat and Zavier (1999) following the Census of India Study and all estimates were generated for each of the geographic regions.This study brings out the stark intra-state and inter-regional disparities in infant and under-five mortality in India over the past two decades. It further reveals, for the first time, that geographic regions that were underprivileged in child nutrition or wealth or female literacy were also likely to be disadvantaged in terms of infant and child survival irrespective of the state to which they belong. While the role of economic status in explaining child malnutrition and child survival has weakened, the effect of mother's education has actually become stronger over time

Characteristics of Different Systems for the Solar Drying of Crops

Solar dryers are used to enable the preservation of agricultural crops, food processing industries for dehydration of fruits and vegetables, fish and meat drying, dairy industries for production of milk powder, seasoning of wood and timber, textile industries for drying of textile materials. The fundamental concepts and contexts of their use to dry crops is discussed in the chapter. It is shown that solar drying is the outcome of complex interactions particular between the intensity and duration of solar energy, the prevailing ambient relative humidity and temperature, the characteristics of the particular crop and its pre-preparation and the design and operation of the solar dryer

Search for strongly interacting massive particles generating trackless jets in proton-proton collisions at s = 13 TeV

A search for dark matter in the form of strongly interacting massive particles (SIMPs) using the CMS detector at the LHC is presented. The SIMPs would be produced in pairs that manifest themselves as pairs of jets without tracks. The energy fraction of jets carried by charged particles is used as a key discriminator to suppress efficiently the large multijet background, and the remaining background is estimated directly from data. The search is performed using proton-proton collision data corresponding to an integrated luminosity of 16.1 fb - 1 , collected with the CMS detector in 2016. No significant excess of events is observed above the expected background. For the simplified dark matter model under consideration, SIMPs with masses up to 100 GeV are excluded and further sensitivity is explored towards higher masses

Evidence for Top Quark Production in Nucleus-Nucleus Collisions

Peer reviewe

Observation of the B-s(0) -> X(3872)phi Decay

Using a data sample of proton-proton collisions at root s = 13 TeV, corresponding to an integrated luminosity of 140 fb(-1) collected by the CMS experiment in 2016-2018, the B-s(0) -> X(3872)phi decay is observed. Decays into J/psi pi(+)pi(-) and K+K- are used to reconstruct, respectively, the X(3872) and phi. The ratio of the product of branching fractions B[B-s(0) -> X(3872)phi]B[X(3872) -> J/psi pi(+)pi(-)] to the product B[B-s(0) ->psi(2S)phi]B[psi(2S) -> J/psi pi(+)pi(-)] is measured to be [2.21 +/- 0.29(stat) +/- 0.17(syst)]%. The ratio B[B-s(0) -> X(3872)phi]/B[B-0 -> X(3872)K-0] is found to be consistent with one, while the ratio B[B-s(0) -> X(3872)phi]/B[B+-> X(3872)K+] is two times smaller. This suggests a difference in the production dynamics of the X(3872) in B-0 and B(0)s meson decays compared to B+. The reported observation may shed new light on the nature of the X(3872) particle.Peer reviewe