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Big data challenge via Tennessee Eastman Process
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Advanced machine learning techniques for video, social and biomedical data analytics
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From archive to analytics: the R-Shief media system and the stories it tells
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A complex event processing framework for fast data management
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Applying adaptive methods and classical scale reduction techniques to data from the big five inventory
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Coded computing: Mitigating fundamental bottlenecks in large-scale data analytics
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Exploiting variable task granularities for scalable and efficient parallel graph analytics
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Big data analytics in metagenomics: integration, representation, management, and visualization
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Complex pattern search in sequential data
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Policy based data placement in distributed systems
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Integrating data analytics and blended quality management to optimize higher education systems (HEES)
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Robust real-time algorithms for processing data from oil and gas facilities
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Architectural innovations for mitigating data movement cost on graphics processing units and storage systems
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Cache analysis and techniques for optimizing data movement across the cache hierarchy
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Using classification and regression trees (CART) and random forests to address missing data
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Probabilistic data-driven predictive models for energy applications
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Adaptive and resilient stream processing on cloud infrastructure
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New analysis methods for microarray data
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Geometric interpretation of biological data: algorithmic solutions for next generation sequencing analysis at massive scale
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Privacy for all: enshrining data privacy as a civil right in the Information Age
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Efficient processing of streaming data in multi-user and multi-abstraction workflows
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Exploring the complexities of private sector influence: the case of student data privacy policy
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Studies into data-driven approaches for nonlinear system identification, condition assessment, and health monitoring
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Analysis of waveform and catalog data of aftershocks for properties of earthquakes and faults
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Shrinkage methods for big and complex data analysis
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