Ashok Srivastava

Member since: Jan 05, 2014, Verizon

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  • Highly Scalable Matching Pursuit Signal Decomposition Algorithm

    A Publication, Ashok Srivastava's Collection - 7 years, 2 months ago

    Shared By: Ashok Srivastava

    In this research, we propose a variant of the classical Matching Pursuit Decomposition (MPD) algorithm with significantly improved scalability and computational performance. MPD is a ...

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  • Data Mining at NASA: From Theory to Applications

    A Publication, Ashok Srivastava's Collection - 7 years, 2 months ago

    Shared By: Ashok Srivastava

    NASA has some of the largest and most complex data sources in the world, with data sources ranging from the earth sciences, space sciences, and ...

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  • Classification of Damage Signatures in Composite Plates using On

    A Publication, Santanu Das's Collection - 10 years, 5 months ago

    Shared By: Santanu Das

    Damage characterization through wave propagation and scattering is of considerable interest to many non-destructive evaluation techniques. For fiber-reinforced composites, complex waves can be generated during ...

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  • Predicting Engine Parameters using the Optical Spectrum

    A Publication, Ashok Srivastava's Collection - 7 years, 2 months ago

    Shared By: Ashok Srivastava

    The Optical Plume Anomaly Detection (OPAD) system is under development to predict engine anomalies and engine parameters of the Space Shuttle's Main Engine (SSME). The ...

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  • Discovery of Recurring Anomalies in Text Reports

    A Publication, Ashok Srivastava's Collection - 7 years, 2 months ago

    Shared By: Ashok Srivastava

    This paper describes the results of a significant research and development effort conducted at NASA Ames Research Center to develop new text mining algorithms to ...

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  • Onboard Detection of Snow, Ice, Clouds, and Other Processes

    A Publication, Ashok Srivastava's Collection - 7 years, 2 months ago

    Shared By: Ashok Srivastava

    The detection of clouds within a satellite image is essential for retrieving surface geophysical parameters from optical and thermal imagery. Even a small percentage of ...

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  • Mixture Density Mercer Kernels: A Method to Learn Kernels

    A Publication, Ashok Srivastava's Collection - 7 years, 2 months ago

    Shared By: Ashok Srivastava

    This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian ...

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  • Characterizing Variability and Multi-Resolution Predictions

    A Publication, Ashok Srivastava's Collection - 7 years, 2 months ago

    Shared By: Ashok Srivastava

    In previous papers, we introduced the idea of a Virtual Sensor, which is a mathematical model trained to learn the potentially nonlinear relationships between spectra ...

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  • Ensemble Approach to Building Mercer Kernels

    A Publication, Ashok Srivastava's Collection - 7 years, 2 months ago

    Shared By: Ashok Srivastava

    This paper presents a new methodology for automatic knowledge driven data mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive ...

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  • Stable and Efficient Gaussian Process Calculations

    A Publication, Ashok Srivastava's Collection - 7 years, 2 months ago

    Shared By: Ashok Srivastava

    The use of Gaussian processes can be an effective approach to prediction in a supervised learning environment. For large data sets, the standard Gaussian process ...

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Ashok's Projects (16)

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