Search NASA⌕ Search

SEARCH · Search NASA

Results for “randomized sampling”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,387 records · Page 77

Ensemble Federated Machine Learning‐Based Cybersecurity Situational Awareness in Microgrid Network

Cyber-physical microgrids are vulnerable to stealthy cybersecurity threats that disguise their actions through the exploitation of system knowledge. Such actions can severely impacts microgrids deployed in defense bases, slowing the response time of military forces during national emergencies. Several machine-learning algorithms have been proposed to detect intrusions in the grid networks; however, these traditional machine-learning algorithms lack data privacy and are subject to several adversarial machine-learning threats. This paper proposes a novel federated machine learning (FML)-based three-model framework to detect and identify stealthy data-integrity attacks while ensuring data privacy in microgrid networks. The proposed architecture uses a variational mode decomposition technique to extract derived features from incoming measurement and control datasets. The extraction of these derived features allows FML models to learn minute variations in data patterns that allow them to perform significantly better than the models trained with generic datasets consisting of raw features. Our experimental results show the efficient performance of the proposed methodology against different types of data integrity attacks while considering primary and secondary controllers in microgrids. Further, the applied FML-integrated random forest ensemble algorithm outperforms the existing generic FML algorithms during noisy and noise-free datasets with prediction latencies of only 91–134 µs per sample within the 0.1 s sampling interval and requires communication bandwidth of around ∼8.25 KB/s at the control center and ∼2.7 KB/s per edge client for communication.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Comparison of venous and pooled capillary hemoglobin levels for the detection of anemia among adolescent girls

Introduction: Blood source is a known preanalytical factor affecting hemoglobin (Hb) concentrations, and there is evidence that capillary and venous blood may yield disparate Hb levels and anemia prevalence. However, data from adolescents are scarce. Objective: To compare Hb and anemia prevalence measured by venous and individual pooled capillary blood among a sample of girls aged 10–19 years from 232 schools in four regions of Ghana in 2022. Methods: Among girls who had venous blood draws, a random subsample was selected for capillary blood. Hb was measured using HemoCue® Hb-301. We used Lin’s concordance correlation coefficient (CCC) to quantify the strength of the bivariate relationship between venous and capillary Hb and a paired t-test for difference in means. We used McNemar’s test for discordance in anemia cases by blood source and weighted Kappa to quantify agreement by anemia severity. A multivariate generalized estimating equation was used to quantify adjusted population anemia prevalence and assess the association between blood source and predicted anemia risk. Results: We found strong concordance between Hb measures (CCC = 0.86). The difference between mean venous Hb (12.8 g/dL, ± 1.1) and capillary Hb (12.9 g/dL, ± 1.2) was not significant (p = 0.26). Crude anemia prevalence by venous and capillary blood was 20.6% and 19.5%, respectively. Adjusted population anemia prevalence was 23.5% for venous blood and 22.5% for capillary ( = 0.45). Blood source was not associated with predicted anemia risk (risk ratio: 0.99, 95% CI: 0.96, 1.02). Discordance in anemia cases by blood source was not significant (McNemar p = 0.46). Weighted Kappa demonstrated moderate agreement by severity (k =0.67). Among those with anemia by either blood source (n = 111), 59% were identified by both sources. Conclusion: In Ghanaian adolescent girls, there was no difference in mean Hb, anemia prevalence, or predicted anemia risk by blood source. However, only 59% of girls with anemia by either blood source were identified as having anemia by both sources. These findings suggest that pooled capillary blood may be useful for estimating Hb and anemia at the population level, but that caution is needed when interpreting individual-level data.

59 BASIC BIOLOGICAL SCIENCES↗

Derivation of aerosol profiles for MC3E convection studies and use in simulations of the 20 May squall line case

Advancing understanding of deep convection microphysics via mesoscale modeling studies of well-observed case studies requires observation-based aerosol inputs. Here, we derive hygroscopic aerosol size distribution input profiles from ground-based and airborne measurements for six convection case studies observed during the Midlatitude Continental Convective Cloud Experiment (MC3E) over Oklahoma. We demonstrate use of an input profile in simulations of the only well-observed case study that produced extensive stratiform outflow on 20 May 2011. At well-sampled elevations between -11 and -23 °C over widespread stratiform rain, ice crystal number concentrations are consistently dominated by a single mode near ~400 µm in randomly oriented maximum dimension ( D max ). The ice mass at -23 °C is primarily in a closely collocated mode, whereas a mass mode near D max ~1000 µm becomes dominant with decreasing elevation to the -11 °C level, consistent with possible aggregation during sedimentation. However, simulations with and without observation-based aerosol inputs systematically overpredict mass peak D max by a factor of 3–5 and underpredict ice number concentration by a factor of 4–10. Previously reported simulations with both two-moment and size-resolved microphysics have shown biases of a similar nature. The observed ice properties are notably similar to those reported from recent tropical measurements. Based on several lines of evidence, we speculate that updraft microphysical pathways determining outflow properties in the 20 May case are similar to a tropical regime, likely associated with warm-temperature ice multiplication that is not well understood or well represented in models.

54 ENVIRONMENTAL SCIENCES↗

Interannual variability and predictability of 500 mb geopotential heights over the Northern Hemisphere

The interannual variability of monthly mean 500 mb heights in a 15-year sample of observed data is compared to the variance expected from sampling errors associated with high-frequency fluctuations using the analysis of variance approach. The monthly mean 'signal' stands out significantly from the 'noise' over a substantial fraction of the Northern Hemisphere during the winter. The expected spectrum of variance at very low frequencies is assumed to be white at frequencies lower than per (30 days) rather than the per (96 days) cutoff used by Madden. This difference is justified by observing that the effective time between independent samples T(0) is relatively insensitive to changes in the maximum lag over which the local autocorrelation is integrated to calculate T(0). Further non-randomness in the variance of 500 mb heights is evidenced by the correlation between monthly mean height and contemporaneous daily variability.

Shukla, J.↗

Longwave radiation parameterization for UCLA/GLAS GCM

This document describes the parameterization of longwave radiation in the UCLA/GLAS general circulation model. Transmittances have been computed from the work of Arking and Chou for water vapor and carbon dioxide and ozone absorptances are computed using a formula due to Rodgers. Cloudiness has been introduced into the code in a manner in which fractional cover and random or maximal overlap can be accommodated. The entire code has been written in a form that is amenable to vectorization on CYBER and CRAY computers. Sample clear sky computations for five standard profiles using the 15- and 9-level versions of the model have been included.

HARSHVARDHAN↗

Large N-body simulations of a universe dominated by cold dark matter

It is shown that pure gravitational evolution from an initial random density field with the standard cold dark matter (CDM) power spectrum does occasionally lead to filaments, walls, and voids remarkably like those seen in observed samples. A problem with the flat CDM model is the degree of streaming of galaxies relative to their velocity dispersion. A biased open CDM model seems to be more compatible with the observational data though it requires a higher amplitude of microwave background fluctuations.

Park, Changbom↗

Radar modeling of a boreal forest

Microwave modeling, ground truth, and SAR data are used to investigate the characteristics of forest stands. A mixed coniferous forest stand has been modeled at P, L, and C bands. Extensive measurements of ground truth and canopy geometry parameters were performed in a 200-m-square hemlock-dominated forest plot. About 10 percent of the trees were sampled to determine a distribution of diameter at breast height (DBH). Hemlock trees in the forest are modeled by characterizing tree trunks, branches, and needles as randomly oriented lossy dielectric cylinders whose area and orientation distributions are prescribed. The distorted Born approximation is used to compute the backscatter at P, L, and C bands. The theoretical results are found to be lower than the calibrated ground-truth data. The experiment and model results agree quite closely, however, when the ratios of VV to HH and HV to HH are compared.

Chauhan, Narinder S.↗

Environmental test program for superconducting materials and devices

A systematic approach to obtaining real time, superconducting YBa2Cu30(7-x) materials is presented. The work was carried out under the overall direction of Clemson University with tasks being performed at both Clemson and Westinghouse (Aiken, SC). Clemson prepared the tapecast superconducting 123 material and fabricated in into substrate-supported, environmentally-protected conducting links. Following this, all of the elements were individually tested for resistance vs. temperature and Tc; and then a portion of them were kept at Clemson for further testing while a randomly selected group was delivered to Westinghouse for specialized testing and evaluation in their low temperature/high vacuum and radiation facilities. In addition, a number of control samples (12 ea.) were put on the shelf at Clemson for further reference at the end of the testing period. The specific tests conducted at Clemson and Westinghouse/SRC are presented with a summary of the results.

Haertling, Gene↗

Characterization of low thermal conductivity PAN-based carbon fibers

The microstructure and surface chemistry of eight low thermal conductivity (LTC) PAN-based carbon fibers were determined and compared with PAN-based fibers heat treated to higher temperatures. Based on wide-angle x ray diffraction, the LTC PAN fibers all appear to have a similar turbostratic structure with large 002 d-spacings, small crystallite sizes, and moderate preferred orientation. Limited small-angle x ray scattering (SAXS) results indicate that, with the exception of LTC fibers made by BASF, the LTC fibers do not have well developed pores. Transmission electron microscopy shows that the texture of the two LTC PAN-based fibers studied (Amoco T350/23X and /25X) consists of multiple sets of parallel, wavy, bent layers that interweave with each other forming a complex three dimensional network oriented randomly around the fiber axis. X ray photoelectron spectroscopy (XPS) analysis finds correlations between heat treated temperatures and the surface composition chemistry of the carbon fiber samples.

Katzman, Howard A.↗

Dynamics of Sheared Granular Materials

This work focuses on the properties of sheared granular materials near the jamming transition. The project currently involves two aspects. The first of these is an experiment that is a prototype for a planned ISS (International Space Station) flight. The second is discrete element simulations (DES) that can give insight into the behavior one might expect in a reduced-g environment. The experimental arrangement consists of an annular channel that contains the granular material. One surface, say the upper surface, rotates so as to shear the material contained in the annulus. The lower surface controls the mean density/mean stress on the sample through an actuator or other control system. A novel feature under development is the ability to 'thermalize' the layer, i.e. create a larger amount of random motion in the material, by using the actuating system to provide vibrations as well control the mean volume of the annulus. The stress states of the system are determined by transducers on the non-rotating wall. These measure both shear and normal components of the stress on different size scales. Here, the idea is to characterize the system as the density varies through values spanning dense almost solid to relatively mobile granular states. This transition regime encompasses the regime usually thought of as the glass transition, and/or the jamming transition. Motivation for this experiment springs from ideas of a granular glass transition, a related jamming transition, and from recent experiments. In particular, we note recent experiments carried out by our group to characterize this type of transition and also to demonstrate/ characterize fluctuations in slowly sheared systems. These experiments give key insights into what one might expect in near-zero g. In particular, they show that the compressibility of granular systems diverges at a transition or critical point. It is this divergence, coupled to gravity, that makes it extremely difficult if not impossible to characterize the transition region in an earth-bound experiment. In the DE modeling, we analyze dynamics of a sheared granular system in Couette geometry in two (2D) and three (3D) space dimensions. Here, the idea is to both better understand what we might encounter in a reduced-g environment, and at a deeper level to deduce the physics of sheared systems in a density regime that has not been addressed by past experiments or simulations. One aspect of the simulations addresses sheared 2D system in zero-g environment. For low volume fractions, the expected dynamics of this type of system is relatively well understood. However, as the volume fraction is increased, the system undergoes a phase transition, as explained above. The DES concentrate on the evolution of the system as the solid volume fraction is slowly increased, and in particular on the behavior of very dense systems. For these configurations, the simulations show that polydispersity of the sheared particles is a crucial factor that determines the system response. Figures 1 and 2 below, that present the total force on each grain, show that even relatively small (10 %) nonuniformity of the size of the grains (expected in typical experiments) may lead to significant modifications of the system properties, such as velocity profiles, temperature, force propagation, and formation shear bands. The simulations are extended in a few other directions, in order to provide additional insight to the experimental system analyzed above. In one direction, both gravity, and driving due to vibrations are included. These simulations allow for predictions on the driving regime that is required in the experiments in order to analyze the jamming transition. Furthermore, direct comparison of experiments and DES will allow for verification of the modeling assumptions. We have also extended our modeling efforts to 3D. The (preliminary) results of these simulations of an annular system in zero-g environment will conclude the presentation.

Kondic, Lou↗

Estimation of Signal Coherence Threshold and Concealed Spectral Lines Applied to Detection of Turbofan Engine Combustion Noise

Combustion noise from turbofan engines has become important, as the noise from sources like the fan and jet are reduced. An aligned and un-aligned coherence technique has been developed to determine a threshold level for the coherence and thereby help to separate the coherent combustion noise source from other noise sources measured with far-field microphones. This method is compared with a statistics based coherence threshold estimation method. In addition, the un-aligned coherence procedure at the same time also reveals periodicities, spectral lines, and undamped sinusoids hidden by broadband turbofan engine noise. In calculating the coherence threshold using a statistical method, one may use either the number of independent records or a larger number corresponding to the number of overlapped records used to create the average. Using data from a turbofan engine and a simulation this paper shows that applying the Fisher z-transform to the un-aligned coherence can aid in making the proper selection of samples and produce a reasonable statistics based coherence threshold. Examples are presented showing that the underlying tonal and coherent broad band structure which is buried under random broadband noise and jet noise can be determined. The method also shows the possible presence of indirect combustion noise. Copyright 2011 Acoustical Society of America. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the Acoustical Society of America.

Miles, Jeffrey Hilton↗

The EVE Doppler Sensitivity and Flare Observations

The Extreme-ultraviolet Variability Experiment (EVE) obtains continuous EUV spectra of the Sun viewed as a star. Its primary objective is the characterization of solar spectral irradiance, but its sensitivity and stability make it extremely interesting for observations of variability on time scales down to the limit imposed by its basic 10 s sample interval. In this paper we characterize the Doppler sensitivity of the EVE data. We find that the 30.4 nm line of He II has a random Doppler error below 0.001 nm (1 pm, better than 10 km/s as a redshift), with ample stability to detect the orbital motion of its satellite, the Solar Dynamics Observatory (SDO). Solar flares also displace the spectrum, both because of Doppler shifts and because of EVE's optical layout, which (as with a slitless spectrograph) confuses position and wavelength. As a flare develops, the centroid of the line displays variations that reflect Doppler shifts and therefore flare dynamics. For the impulsive phase of the flare SOL2010-06-12, we find the line centroid to have a redshift of 16.8 +/- 5.9 km/s relative to that of the flare gradual phase (statistical errors only). We find also that high-temperature lines, such as Fe XXIV 19.2 nm, have well-determined Doppler components for major flares, with decreasing apparent blueshifts as expected from chromospheric evaporation flows.

Hudson, H. S.↗

Mapping National Forest Aboveground Biomass in Mexico By Integrating GEDI and Landsat Times Series Data

Mexico is one of the countries with great potential for the UN's Reducing Emissions from Deforestation and Forest Degradation (REDD+) program, a key nature-based solution for the forest sector. To monitor carbon stock changes, there is a growing demand for unbiased Monitoring Reporting Verification (MRV) systems to facilitate effective forest management and climate change mitigation strategies. Remote sensing-based national aboveground biomass density (AGBD) estimation over Mexico is scarce and often limited to one-time static mapping, leading to spatiotemporal inconsistency in inputs. As an effort under NASA's Carbon Monitoring System (CMS) program, we have developed a remote sensing-based approach to create consistent historical AGBD maps of Mexico using multi-stream remote sensing data, including spaceborne lidar GEDI and long-term Landsat time series, as well as topographic information. We employ the continuous change detection and classification (CCDC) algorithm for temporal modeling of Landsat surface reflectance, followed by the inference of forest AGBD using a random forest machine learning algorithm with the temporal information of land surface dynamics extracted by the CCDC as input. GEDI provides unprecedented forest structure and AGBD sampling datasets for model training and validation practices. In this presentation, we share the progress made in developing a spatially explicit mapping of historical AGBD changes associated with land surface changes and post-disturbance landscapes.

Taejin Park↗

A Predictive Model for Survival of Escherichia coli O157:H7 and Generic E. coli in Soil Amended with Untreated Animal Manure

Abstract This study aimed at developing a predictive model that captures the influences of a variety of agricultural and environmental variables and is able to predict the concentrations of enteric bacteria in soil amended with untreated Biological Soil Amendments of Animal Origin (BSAAO) under dynamic conditions. We developed and validated a Random Forest model using data from a longitudinal field study conducted in mid‐Atlantic United States investigating the survival of Escherichia coli O157:H7 and generic E. coli in soils amended with untreated dairy manure, horse manure, or poultry litter. Amendment type, days of rain since the previous sampling day, and soil moisture content were identified as the most influential agricultural and environmental variables impacting concentrations of viable E. coli O157:H7 and generic E. coli recovered from amended soils. Our model results also indicated that E. coli O157:H7 and generic E. coli declined at similar rates in amended soils under dynamic field conditions.The Random Forest model accurately predicted changes in viable E. coli concentrations over time under different agricultural and environmental conditions. Our model also accurately characterized the variability of E. coli concentration in amended soil over time by providing upper and lower prediction bound estimates. Cross‐validation results indicated that our model can be potentially generalized to other geographic regions and incorporated into a risk assessment for evaluating the risks associated with application of untreated BSAAO. Our model can be validated for other regions and predictive performance also can be enhanced when data sets from additional geographic regions become available.

Pang, Hao↗

Magnetism in Mixed Valence, Defect, Cubic Perovskites: BaIn 1– x Fe x O 2.5+δ , x = 0.25, 0.50, and 0.75. Local and Average Structures

The series BaIn 1–x Fe x O 2.5+δ , x = 0.25, 0.50, and 0.75, has been prepared under air-fired and argon-fired conditions and studied using X-ray diffraction, d.c. and a.c. susceptibility, Mössbauer spectroscopy, neutron diffraction, X-ray near edge absorption spectroscopy (XANES), and X-ray pair distribution (PDF) methods. While Ba 2 In 2 O 5 (BaInO 2.5 ) crystallizes in an ordered brownmillerite structure, Ibm2, and Ba 2 Fe 2 O 5 (BaFeO 2.5 ) crystallizes in a complex monoclinic structure, P2 1 /c, showing seven Fe 3+ sites with tetrahedral, square planar, and octahedral environments, all phases studied here crystallize in the cubic perovskite structure, Pm$\bar{}3}$m, with long-range disorder on the small cation and oxygen sites. 57 Fe Mössbauer studies indicate a mixed valency, Fe 4+ /Fe 3+ , for both the air-fired and argon-fired samples. The increased Fe 3+ content for the argon-fired samples is reflected in increased cubic cell constants and in the increased Mössbauer fraction. It appears that the Pm$\bar{}3}$m phases are only metastable when fired in argon. From a slightly modified percolation theory for a primitive cubic lattice (taking into account the presence of random O atom vacancies), long-range spin order is permitted for the x = 0.50 and 0.75 phases. Instead, the d.c. susceptibility shows only zero-field-cooled (ZFC) and field-cooled (FC) divergences at ~6 K [5 K] for x = 0.50 and at ~22 K [21 K] for x = 0.75, with values for the argon-fired samples in [ ]. Neutron diffraction data for the air-fired samples confirm the absence of long-range magnetic order at any studied temperature. For the air-fired x = 0.50, a.c. susceptibility data show a frequency-dependent χ'(max) and spin glass behavior, while for x = 0.75, χ'(max) is invariant with frequency, ruling out either a spin glass or a superparamagnetic ground state. These behaviors are discussed in terms of competing Fe 3+ –Fe 3+ antiferromagnetic exchange and ferromagnetic Fe 3+ –Fe 4+ exchange. The PDF and 57 Fe Mössbauer data indicate a local structure at short interatomic distances, which deviates strongly from the average Pm$\bar{}3}$m model. Fe Mössbauer, PDF, and XANES data show a systematic dependence on x and indicate that the Fe 3+ sites are largely fourfold-coordinated and Fe 4+ sites are fivefold- or sixfold-coordinated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Photometric classification of type Ia supernovae in the SuperNova Legacy Survey with supervised learning

In the era of large astronomical surveys, photometric classification of supernovae (SNe) has become an important research field due to limited spectroscopic resources for candidate follow-up and classification. In this work, we present a method to photometrically classify type Ia supernovae based on machine learning with redshifts that are derived from the SN light-curves. This method is implemented on real data from the SNLS deferred pipeline, a purely photometric pipeline that identifies SNe Ia at high-redshifts (0.2 < z < 1.1). Our method consists of two stages: feature extraction (obtaining the SN redshift from photometry and estimating light-curve shape parameters) and machine learning classification. We study the performance of different algorithms such as Random Forest and Boosted Decision Trees. We evaluate the performance using SN simulations and real data from the first 3 years of the Supernova Legacy Survey (SNLS), which contains large spectroscopically and photometrically classified type Ia samples. Using the Area Under the Curve (AUC) metric, where perfect classification is given by 1, we find that our best-performing classifier (Extreme Gradient Boosting Decision Tree) has an AUC of 0.98.We show that it is possible to obtain a large photometrically selected type Ia SN sample with an estimated contamination of less than 5%. When applied to data from the first three years of SNLS, we obtain 529 events. We investigate the differences between classifying simulated SNe, and real SN survey data. In particular, we find that applying a thorough set of selection cuts to the SN sample is essential for good classification. This work demonstrates for the first time the feasibility of machine learning classification in a high- z SN survey with application to real SN data.

79 ASTRONOMY AND ASTROPHYSICS↗

Resistance Exercise and Inflammation in Breast Cancer Patients Undergoing Adjuvant Radiation Therapy: Mediation Analysis From a Randomized, Controlled Intervention Trial

Purpose: To explore the mediating role of inflammatory parameters in the development of fatigue, pain, and potentially related depressive symptoms during radiation therapy for breast cancer and its mitigation by resistance exercise. Methods and Materials: Breast cancer patients scheduled for adjuvant radiation therapy were randomized to 12-week progressive resistance exercise training (EX) or a relaxation control group. Interleukin-6 (IL-6) and interleukin-1 receptor antagonist (IL-1ra) were measured in serum samples collected before, at the end, and 6 weeks after radiation therapy from 103 chemotherapy-naïve participants. Fatigue was assessed with the multidimensional Fatigue Assessment Questionnaire, pain with the European Organization for Research and Treatment of Cancer QLQ-C30, and depressive symptoms with the Center for Epidemiologic Studies Depression Scale. Analysis of covariance models, partial correlations, Freedman-Schatzkin tests, and R{sup 2} effect-size measures for mediation were calculated. Results: The analysis of covariance models revealed a significant intervention effect on IL-6 (P=.010) and the IL-6/IL-1ra ratio (P=.018), characterized by a marked increase during radiation therapy among controls, but no significant change in EX. Interleukin-1 receptor antagonist did not change significantly in either group (P=.88). Increased IL-6 and IL-6/IL-1ra levels at the end of radiation therapy were significantly associated with increased physical fatigue and pain 6 weeks after radiation. We observed significant partial mediation by IL-6 and IL-6/IL-1ra of the effect of resistance exercise on physical fatigue (Freedman-Schatzkin P=.023 and P<.001) and pain (both P<.001). Hereby IL-6 and IL-6/IL-1ra mediated between 15% and 24% of the variance of physical fatigue and pain explained by the intervention. Conclusions: This randomized, controlled trial showed a significantly increased proinflammatory cytokine level after adjuvant radiation therapy in breast cancer patients. This effect was counteracted by progressive resistance exercise training. Interleukin-6 and the IL-6/IL-1ra ratio seemed to mediate the beneficial effect of exercise on physical fatigue and pain but only to a small extent.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DeepHyper: Asynchronous Hyperparameter Search for Deep Neural Networks

Hyperparameters employed by deep learning (DL) methods play a substantial role in the performance and reliability of these methods in practice. Unfortunately, finding performance-optimizing hyperparameter settings is a notoriously difficult task. Hyperparameter search methods typically have limited production-strength implementations or do not target scalability within a highly parallel machine, portability across different machines, experimental comparison between different methods, and tighter integration with workflow systems. In this paper, we present DeepHyper, a Python package that provides a common interface for the implementation and study of scalable hyperparameter search methods. It adopts the Balsam workflow system to hide the complexities of running large numbers of hyperparameter configurations in parallel on high-performance computing (HPC) systems. We implement and study asynchronous model-based search methods that consist of sampling a small number of input hyperparameter configurations and progressively fitting surrogate models over the input-output space until exhausting a user-defined budget of evaluations. We evaluate the efficacy of these methods relative to approaches such as random search, genetic algorithms, Bayesian optimization, and hyperband on DL benchmarks on CPU- and GPU-based HPC systems.

Balaprakash, Prasanna↗