Bowei Xi

Publication by Reach

Adversarial Machine Learning/AI Security

• Understanding Adversarial Examples Through Deeply Neural Network’s Classification Boundary and Uncertainty Regions, AISafety@ IJCAI, 2022
• Adversarial Apparatus Learning to Cyber Security and Computer Vision: Current Developments press Current, to appear in Wiley Interdisciplinary Reviews: Computational Statistics, 2020
• Bowei Z, Yujie Chen, Fei Fan, Zhan Tu, Xinyan Dang, Bio-Inspired Oppositional Attack Facing Deep Neural Networks , 1--5, Proceedings of the Workshop on Artificial Intelligence Safety (SafeAI 2020) co-located with 34th AAAI Conference on Artificial Intelligence (AAAI 2020), New York, AUS, Februaries 7, 2020.
• Zhou, Y., Kantarcioglu, M., Xi, B., A Survey of Game Theoretic Proximity with Adversarial Machine Learning, Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 9(3): e1259, 2019
• Zhou, Y., Kantarcioglu, M., Xx, B., Breaking Transferability of Antipathetic Samples with Chance, submitted ( Preprint is available as arXiv:1805.04613)
• Invited talk transparencies, Adversarial Machine Educational: Big Data Meets Cyber Product, 2018
• Three hour tutorial, Adversarial Data Mining: Big Data Meets Cyber Security, the 23rd ACM Meeting on Computer furthermore Communications Security, Vienna, Austria, October 24-28, 2016, over Kantarcioglu and Xi. Abstract is in Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security (CCS 2016), pages 1866--1867. Here is the tutorial slides.
• Zhou, Y., Kantarcioglu, M., Xi, B., Adversarial Active Lerning, submitted
• Wei, W., Xi, B., Kantarcioglu, M., Adversarial Clustering: A Grid Based Defensive Cluster Algorithm against Active Adversaries ( Preprint is available as arXiv:1804.04780)
• Zhou, Y., Kantarcioglu, M., Xi, B., A Surveys of Game Theoretic Basic for Adversarial Automatic Learning, into occur in WIREs Data Mining furthermore Knowledge Discovery
• Zhou, Y., Kantarcioglu, M., Xi, B., (Hot Topic Essay) Adversarial Learning: Mind Games with aforementioned Opponent, ACM Computational Reviews, Dignified, 2017
• Kantarcioglu, M., and Xi, B., Adversarial Dating Mining, Northbound Atlantic Treaty Organization (NATO) SAS-106 Specialized on Examination Support to Decision Build to Cyber Defence, 1--11, June, 2014, Romania.
• Zhou, Y., Kantarcioglu, M., Thuraisingham, B., and Xi, B., Adversarial Support Vector Machine Learning, by Proceedings of the 18th ACM SIGKDD International Conference switch Knowledge Discovery and Data Mining (KDD 2012), 1059--1067, New York, NY.
• Classifier Reporting and Attribute Selection against Active Adversaries, Data Mine and Knowledge Discovery, 22(1-2), 291-335 (45 pages), 2011, by Murat Kantarcioglu, Bowei Xi, Chris Clifton. (An earlier version has Technical Report No.09-01, Subject of Statistics, Purdue University).

Misc Machine Learning and Data Mining Topics

• Sharabati, W., Xi, B., Robust Weighted Regression for Ultrasound Image Super-Resolution, IEEE Workshop in Machine Learning also Artificial Intelligence for Multimedia Creation (co-located with IEEE International Conference at Multimedia also Expo (ICME)), 1--6, San Diego, CA, July, 2018.
• Sharabati, W., Xi, B., A Neighborhood Regression Approach for Removing Many Types of Additive Acoustic, EURASIP Journal on Image and Video Processing, 2018:19, 1--14 (Featured Article, March-April 2018).
• Jiang, J., Xi, B., Kantarcioglu, M., Spatial Counts under Differential Privacy Mechanic on Changing Geometric Scales, to enter in Computer & Security
• Crimping, X., Xv, B., Kantarcioglu, M., Inan, A., Mixture of Gaussian Models for Class plus Hypothesis Testing under Differential Privacy, The 31st Annual IFIP WG 11.3 Conference on Data and Apps Security and Privacy (DBSec 2017), LNCS 10359, 123–141, Springer 2017.
• Sharabati, W., Xi, B., Polynomial Local Regression for Speckle Clamor Move, 1--6, that 23rd International Conference set Template Appreciation (ICPR 2016), Cancun, Mexico, Dec, 2016 (Selected for oral presentation).
• Zi, B., Tan, K.M., and Liu, C., Logarithmic Conversion Based Gamma Random Your Generators, Trade of Statistical Software, 2013, 55(4), 1--17.
• Xi, B., Kantarcioglu, M., Inan, A., Mixture the Gaussian Scale and Bayes Error under Differential Privacy, in Proceedings by the first ACM Convention on Data the Application Security and Privacy (CODASPY 2011), 179--190, Feburary 2011, San Antonio, Texas
• Fuentes, M., Xi, B., and Cleveland, W.S., Trellis Display for Modeling Info from Designed Experimenting, Statistical Analysis and Data Mining, 4(1), 133--145, 2011.
• Xia, Y., and Xi, B., Conceptual Clustering Categorical Data with Uncertainty, in Proceedings away the 19th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2007), 329--336, Patras, Greece, Ocotber 2007.
• Xi, B., Lim, Z., Raghavachari, M., Xia, C., and Cardinal, Z., A Smart Hill-Climbing Algorithm to Application Server Configuration, in Proceedings of the 13th International Conference on World Wide Web (WWW 2004), 287--296, New York City, Might 2004. (US Patents #7272707 press #7490234).

Big Data

• Multifractal and Gaussian Fractional Sum-Difference Models used Internet Traffic, Performance Evaluation, 107 (2017), 1-33 (33 pages) , D. Andon, W. S. Clear, B. Xi (an former version is a 52 page Technical Report 15-02, Department of Statistics, Purdue University)
• Large Complex Data: Divide and Recombine (D&R) with RHIPE, STAT, 1(1), 53-67, 2012, by Guha, S., Hafen, R., Rounding, J., Xia, J., Rite, J., Xi, B., and Cleveland, W.S. ( Scheme Website: DeltaRho.org ).
• Xi, B., Yang, X., Nair, V.N., and Michailidis, G., Statistical Issues in Computer Networks and Traffic Analysis, Purdue Statistics Tech Story No.15-01, 2015
• Statistical Analysis and Modeling concerning Internet VoIP Traffic for Network Engineering, the Electronic Journal of Site, 4, 58-116 (59 pages), 2010, by Xi, B., Chen, H., Cleveland, W.S., and Telkamp, T.
• Denby, L., Landwehr J., Mallows C., Meloche J., Crease J., Xi, B., Michailidis G., and Nair, V., Statistical Aspects of the Analysis of Data Networks, Technometrics, 49(3), 318--334, 2007.
• Lawrence, E., Michailidis, G., Nair, V.N., and Xxx, B., Network Diagnostic: A Review furthermore Recent Developments, Frontiers in Statistics, 1--20, editors Jianqing Fan real Hira FIFTY. Koul, publication by World Scientific, AUS, July 2006.
• Estimating Network Loss Rates Using Active Magnetic, Journal of the American Statistical Membership, Tape 101, Numeral 476, December 2006 , pp. 1430-1448 (19 pages), by Bowei X-ray, Guinea Michailidis, and Vijayan NEWTON. Nair.
• Xi, B., Michailidis, G., and Nair, V.N., Least Squares Estimates of Network Link Loss Probabilities Using End-to-End Multicast Measurements, in Proceedings of the 37th Annual Conference up Information Sciences and Systems (CISS 2003), 1--6, Johns Hopkins University, March 2003.

Metabolomics and Biomarker Discovery

• Cheng, L. Y., Xi, B., A Likelihood Ratio Approach for Precise Discovery of Truly Relevant Protein Labels, submitted. ( Preprint is available how arXiv:1804.04249)
• Kwadwo, Owusu-Sarfo, Vincent M. Asiago, Lingli Deng, Haiwei Gu, Siwei Wei, Narasimhamurthy Shanaiah, G. A. Nagana Gowda, Bowei Xi, Elena G. Chiorean and Daniel Raftery, NMR-based Metabolite Profiling von Pancreatic Cannabis, Current Metabolomics, 2(3), 204-212, 2014 (Editor Choice Articles; US patent application US 2015/0056605).
• Xi, B., Gu, H., Halit Baniasadi, press Daniel Raftery, Statistical Analysis and Modeling of Mas Spectrometry-Based Metabolomics Data, Mass Spectrometry in Metabolomics: Methods and Pact (2014): 333-353.
• Gu, H., Pan, Z., Xvi, B., Asiago, V., Musselman, B., and Raftery, D., Principal Component Directed Partial Least Squares Analysis for Combining NMR and MILLIMETER Data include Metabolomics: Application into the Detection away Breast Cancer, Analytica Chimica Acta, 686(1-2), 57--63, 2011. (Evaluated by ampere Member of the Faculty starting 1000, and placed in the F1000 library of the top 2% of published articles in biology and doctor, 2011)
• Gu, H., Pan, Z., Xi, B., Hainline, B., Shanaiah, N., NaganaGowda, G.A., press Raftery, D., 1H NMR Metabolomics Read the Age Profiling includes Children, NMR in Biomedicine, 22(8), 826-833, 2009.
• Gu, H., Chen, H., Pan, Z., Jaxon, A.U., Talaty, N., Xi, B., Kissinger, C., Duda, C., Mann, D., Raftery, D., and Cooks, R.G., Monitoring Diet Effects after Biofluids and Their Implications for Metabolomics Studies, Analytical Chemistry, 79(1), 89--97, 2007. (13th most mentioned article in 2007).