Bin Li
Orcid: 0000-0003-0831-092XAffiliations:
- Louisiana State University, Department of Experimental Statistics, Baton Rouge, LA, USA
- Ohio State University, Department of Statistics Columbus, OH, USA (PhD 2006)
According to our database1,
Bin Li
authored at least 33 papers
between 2008 and 2024.
Collaborative distances:
Collaborative distances:
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Bibliography
2024
Soil Fertility Prediction Using Combined USB-microscope Based Soil Image, Auxiliary Variables, and Portable X-Ray Fluorescence Spectrometry.
CoRR, 2024
2023
A Smartphone-Enabled Imaging Device for Chromotropic Acid-Based Measurement of Nitrate in Soil Samples.
Sensors, September, 2023
2022
Commun. Stat. Simul. Comput., 2022
Using Nix color sensor and Munsell soil color variables to classify contrasting soil types and predict soil organic carbon in Eastern India.
Comput. Electron. Agric., 2022
2021
2020
Spatially Explicit Model for Statistical Downscaling of Satellite Passive Microwave Soil Moisture.
IEEE Trans. Geosci. Remote. Sens., 2020
Frontiers Comput. Sci., 2020
Comput. Electron. Agric., 2020
2017
Stat. Anal. Data Min., 2017
2016
J. Supercomput., 2016
2015
A framework for evaluating comprehensive fault resilience mechanisms in numerical programs.
J. Supercomput., 2015
Powering Up Dark Silicon: Mitigating the Limitation of Power Delivery via Dynamic Pin Switching.
IEEE Trans. Emerg. Top. Comput., 2015
Cross-architecture prediction based scheduling for energy efficient execution on single-ISA heterogeneous chip-multiprocessors.
Microprocess. Microsystems, 2015
Proceedings of the 2015 IEEE International Symposium on Performance Analysis of Systems and Software, 2015
2014
Comprehensive and Efficient Design Parameter Selection for Soft Error Resilient Processors via Universal Rules.
IEEE Trans. Computers, 2014
Design configuration selection for hard-error reliable processors via statistical rules.
Microprocess. Microsystems, 2014
Proceedings of the Fifteenth International Symposium on Quality Electronic Design, 2014
2013
Predicting Architectural Vulnerability on Multithreaded Processors under Resource Contention and Sharing.
IEEE Trans. Dependable Secur. Comput., 2013
2012
Stat. Anal. Data Min., 2012
Optimal microarchitectural design configuration selection for processor hard-error reliability.
Proceedings of the Thirteenth International Symposium on Quality Electronic Design, 2012
2011
Proceedings of the Sixth International Conference on Networking, Architecture, and Storage, 2011
Universal rules guided design parameter selection for soft error resilient processors.
Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software, 2011
Architecture comparisons between Nvidia and ATI GPUs: Computation parallelism and data communications.
Proceedings of the 2011 IEEE International Symposium on Workload Characterization, 2011
Proceedings of the 2011 IEEE International Symposium on Workload Characterization, 2011
Proceedings of the IEEE 29th International Conference on Computer Design, 2011
Proceedings of the 2011 International Green Computing Conference and Workshops, 2011
2010
Efficient Microarchitectural Vulnerabilities Prediction Using Boosted Regression Trees and Patient Rule Inductions.
IEEE Trans. Computers, 2010
A Host-Based Intrusion Detection System Using Architectural Features to Improve Sophisticated Denial-of-Service Attack Detections.
Int. J. Inf. Secur. Priv., 2010
2009
Accurate and efficient processor performance prediction via regression tree based modeling.
J. Syst. Archit., 2009
Versatile prediction and fast estimation of Architectural Vulnerability Factor from processor performance metrics.
Proceedings of the 15th International Conference on High-Performance Computer Architecture (HPCA-15 2009), 2009
A case study: Using architectural features to improve sophisticated denial-of-service attack detections.
Proceedings of the 2009 IEEE Symposium on Computational Intelligence in Cyber Security, 2009
2008
Comput. Stat. Data Anal., 2008
Efficient mart-aided modeling for microarchitecture design space exploration and performance prediction.
Proceedings of the 2008 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, 2008