Publications

Arxiv

Journals

  1. Stealthy Adversarial Attacks on Machine Learning-Based Classifiers of Wireless Signals
    W. Zhang, M. Krunz and G. Ditzler
    IEEE Transactions on Machine Learning in Communications and Networking, vol. 2., pp. 261-279, 2024.
  2. Knowledge Distillation Under Ideal Joint Classifier Assumption
    H. Li, X. Chen, G. Ditzler, P. Chang, J. Roveda, and A. Li
    Neural Networks, vol. 173, 2024. (arXiv:2304.11004)
  3. ProtoShotXAI: Using Prototypical Few-Shot Architecture for Explainable AI
    S. Hess and G. Ditzler
    Journal of Machine Learning Research, 24(325):1−49, 2023.
  4. DeScoD-ECG: Deep Score-Based Diffusion Model for ECG Baseline Wander and Noise Removal
    H. Li, G. Ditzler, J. Roveda and A. Li
    IEEE Journal of Biomedical and Health Informatics, 2023. (arXiv:2208.00542)
  5. Ovarian Cancer Detection Using Optical Coherence Tomography and Convolutional Neural Networks
    D. Schwartz, T. Sawyer, N. Thurston, J. Barton and G. Ditzler
    Neural Computing and Applications, vol. 34, no. 11, pp. 8977-8987, 2022.
  6. Attack Transferability Against Information-Theoretic Feature Selection
    S. Gupta, R. Golota and G. Ditzler
    IEEE Access, 2021, vol. 9, pp. 115885-115894.
  7. Data Poisoning Against Information-Theoretic Feature Selection
    H. Liu and G. Ditzler
    Information Sciences, 2021, vol. 573, pp. 396-411.
  8. A Convolutional Neural Network-enabled Pavement Roughness Assessment using Non-calibrated Vehicle Dynamic Responses
    J.-H. Jeong, H. Jo, and G. Ditzler
    Computer-Aided Civil and Infrastructure Engineering, 2020.
  9. Learning What We Don’t Care About: Regularization with Sacrifical Functions
    G. Ditzler, S. Miller, and J. Rozenblit
    Information Sciences, 2019, vol. 496, pp. 198-211.
  10. A Semi-Parallel Framework for Greedy Information-Theoretic Feature Selection
    H. Liu and G. Ditzler
    Information Sciences, 2019, vol. 492, pp. 13-28.
  11. Approximate Kernel Reconstruction for Time-Varying Networks
    G. Ditzler, N. Bouaynaya, R. Shterenberg, and H. M. Fathallah Shaykh
    BMC BioData Mining, 2019, vol. 12, no. 9.
  12. A Novelty Detector and Extreme Verification Latency Model for Nonstationary Environments
    R. Razavi-Far, E. Hallaji, M. Saif, and G. Ditzler
    IEEE Transactions on Industrial Electronics, 2019, vol. 66, no. 1, pp. 561-570.
  13. Weight normalization with spiking neural networks
    Z. Liang, D. Schwartz, G. Ditzler, and O. Ozan Koyluoglu
    Neural Networks, 2018, vol. 108, pp. 365-378.
  14. AKRON: An Algorithm for Approximating Sparse Kernel Reconstruction
    G. Ditzler, N. Bouaynaya, and R. Shterenberg
    Signal Processing, vol. 144, 2018, pp. 265-270.
  15. Improvements to Scalable Online Feature Selection Using Bagging and Boosting
    G. Ditzler, J. LaBarck, J. Ritchie, G. Rosen, and R. Polikar
    IEEE Transactions on Neural Networks and Learning Systems, 2018. vol. 29, no. 9, pp. 4504-4509
  16. A Sequential Learning Approach for Scaling up Filter-Based Feature Subset Selection
    G. Ditzler, R. Polikar, and G. Rosen
    IEEE Transactions on Neural Networks and Learning Systems, 2018, vol. 29, no. 6, pp. 2530-2544.
  17. Fizzy: Feature selection for metagenomics
    G. Ditzler, J. Calvin Morrison, Y. Lan, and G. Rosen
    BMC Bioinformatics, 2015, vol 16, no. 358.
  18. Multi-Layer and Recursive Neural Networks for Metagenomic Classification
    G. Ditzler, R. Polikar, and G. Rosen
    IEEE Transactions on Nanobioscience, 2015, vol. 14, no. 6, pp. 608-616.
  19. Adaptive strategies for learning in nonstationary environments: a survey
    G. Ditzler, M. Roveri, C. Alippi, and R. Polikar
    IEEE Computational Intelligence Magazine, 2015, vol. 10, no. 4, pp. 12-25.
  20. A bootstrap based Neyman-Pearson test for identifying variable importance
    G. Ditzler, R. Polikar, and G. Rosen
    IEEE Transactions on Neural Networks and Learning Systems, 2015, vol. 26, no. 4, pp. 880-886.
  21. Incremental learning of concept drift from streaming imbalanced data
    G. Ditzler and R. Polikar
    IEEE Transactions on Knowledge & Data Engineering, 2013, vol. 25, no. 10, pp. 2283–2301.

Conferences

  1. A Curriculum Learning Framework to Boost Object Detection on Unmanned Aerial Objects
    E. Aslan, K. Naddeo, Taha Bouhsine, R. Polikar, and G. Ditzler
    IEEE Symposium on Computational Intelligence in Security, Defence and Biometrics, 2025.
  2. Boosting Aerial Object Detection Performance via Virtual Reality Data and Multi-Object Training
    N. Koutsoubis, K. Naddeo, G. Williams, G. Lecakes, T. Kiel, G. Ditzler, and N. Bouaynaya
    IEEE/INNS International Joint Conference on Neural Networks, 2023. (talk)
  3. DyViR: Dynamic Virtual Reality Dataset for Aerial Threat Object Detection
    N. Koutsoubis, K. Naddeo, G. Williams, G. Lecakes, A. Almon, T. Kiel, G. Ditzler, and N. Bouaynaya
    SPIE Defense + Commercial Sensing Meeting Information: Synthetic Data for Artificial Intelligence and Machine Learning: Tools, Techniques, and Applications, 2023. (talk)
  4. On Reducing Adversarial Vulnerability with Data Dependent Stochastic Resonance
    D. Schwartz and G. Ditzler
    IEEE Symposium Series on Computational Intelligence, 2022. (talk)
  5. Application of Adversarial Machine learning in Protocol and Modulation Misclassification
    M. Krunz, W. Zhang, and G. Ditzler
    Proceedings of the SPIE, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications IV, 2022. [talk]
  6. Targeted Data Poisoning Attacks Against Continual Learning Neural Networks
    H. Li and G. Ditzler
    IEEE/INNS International Joint Conference on Neural Networks, 2022.
  7. Inter-Architecture Portability of Artificial Neural Networks and Side Channel Attacks
    M. Gopale, G. Ditzler, R. Lysecky and J. Roveda
    Great Lakes Symposium on VLSI (GLSVLSI), 2022.
  8. Intelligent Jamming of Deep Neural Network Based Signal Classification for Shared Spectrum
    W. Zhang, M. Krunz, and G. Ditzler
    Military Communications Conference (MILCOM), 2021.
  9. Multi-Layer Mapping of Cyberspace for Intrusion Detection
    S. Shao, P. Satam, S. Satam, K. AI-Awady, G. Ditzler, S. Hariri, and C. Tunc
    ACS/IEEE International Conference on Computer Systems and Applications, 2021.
  10. Adversarial Filters for Secure Modulation Classification
    A. Berian, K. Staab, G. Ditzler, T. Bose, and R. Tandon
    Asilomar Conference on Signals, Systems and Computers, 2021.
  11. Bolstering Adversarial Robustness with Latent Disparity Regularization
    D. Schwartz and G. Ditzler
    IEEE/INNS International Joint Conference on Neural Networks, 2021.
  12. OrderNet: Sorting High Dimensional Low Sample Data with Few-Shot Learning
    S. Hess and G. Ditzler
    IEEE/INNS International Joint Conference on Neural Networks, 2021. (talk)
  13. A Light-Weight Monocular Depth Estimation With Edge-Guided Occlusion Fading Reduction
    K.-S. Peng, G. Ditzler, and J. Rozenblit
    International Symposium on Visual Computing, 2020.
  14. Bypassing Temporal Dependency in Adversarial Audio Examples
    H. Liu and G. Ditzler
    IEEE Symposium Series on Computational Intelligence, 2020. (talk)
  15. Detecting Adversarial Audio via Activation Quantization Error
    H. Liu and G. Ditzler
    IEEE/INNS International Joint Conference on Neural Networks, 2020. (talk)
  16. Self-Supervised Correlational Monocular Depth Estimation using ResVGG Network
    K.S. Peng, G. Ditzler and J. Rozenblit
    International Conference on Intelligent Systems and Image Processing, 2019.
  17. Poisoning mRMR with Adversarial Data
    H. Liu and G. Ditzler
    IEEE International Conference on Acoustics, Speech and Signal Processing, 2019.
  18. Online Reconfigurable Antenna State Selection based on Thompson Sampling
    T. Zhao, G. Ditzler, and M. Li
    International Conference on Computing, Networking and Communications, 2019.
  19. The Impact of an Adversary in a Language Model
    Z. Liang and G. Ditzler
    IEEE Symposium Series on Computational Intelligence, 2018. (talk)
  20. Malicious HTML File Prediction: A Detection and Classification Perspective with Noisy Data
    S. Hess, P. Satam, G. Ditzler and S. Hariri
    ACS/IEEE International Conference on Computer Systems and Applications, 2018.
  21. Nonlinear Brain Tumor Model Estimation with Long Short-Term Memory Neural Networks
    J. Guo, Z. Liang, E. Scribner, G. Ditzler, N. Bouaynaya and H. Fathallah-Shaykh
    IEEE/INNS International Joint Conference on Neural Networks, 2018.
  22. Fine Tuning Lasso in an Adversarial Environment Against Gradient Attacks
    G. Ditzler and A. Prater
    IEEE Symposium Series on Computational Intelligence, 2017. (talk)
  23. Speeding Up Joint Mutual Information Feature Selection with an Optimization Heuristic
    H. Liu and G. Ditzler
    IEEE Symposium Series on Computational Intelligence, 2017.
  24. Framework to Support DDDAS Decision” Support Systems: Design Overview
    G. Ditzler, A. Akoglu, and S. Hariri
    Workshop on InfoSymbiotics: DDDAS Dynamic Data Driven Applications Systems, 2017.
  25. A Self-Protection Agent using Error Correcting Output Codes to Secure Computers and Applications
    F. de la Pena Montero, S. Hariri, and G. Ditzler
    IEEE International Conference on Cloud and Autonomic Computing, 2017.
  26. Autonomic Management of 3D Cardiac Simulations
    E. Esmaili, A. Akoglu, G. Ditzler, S. Hariri, J. Szep and T. Moukabary
    IEEE International Conference on Cloud and Autonomic Computing, 2017. (best paper award)
  27. Fraud Analysis Approaches in the Age of Big Data - A Review of State of the Art
    S. Makki, R. Haque, Y. Taher, Z. Assaghir, G. Ditzler, M.-S. Hacid and H. Zeineddine
    International Workshop on Autonomic Systems for Big Data Analytics, 2017.
  28. A Fast Information-theoretic Approximation of Joint Mutual Information Feature Selection
    H. Liu and G. Ditzler
    IEEE/INNS International Joint Conference on Neural Networks, 2017.
  29. The AKRON-Kalman Filter for Tracking Time-Varying Networks
    V. Carluccio, N. Bouaynaya, G. Ditzler, and H. M. Fathallah Shaykh
    IEEE International Conference on Biomedical and Health Informatics, 2017.
  30. A Study of Incremental Spectral Meta-Learning for Nonstationary Environments
    G. Ditzler
    IEEE/INNS International Joint Conference on Neural Networks, 2016. (talk)
  31. Scaling a Neyman-Pearson subset selection approach via heuristics for mining massive data
    G. Ditzler, M. Austen, R, Polikar, and G. Rosen
    IEEE Symposium on Computational Intelligence in Data Mining, 2014. (travel award) (talk)
  32. Feature Subset Selection for Inferring Relative Importance of Taxonomy
    G. Ditzler and G. Rosen
    ACM International Workshop on Big Data in Life Sciences, 2014. (invited and travel award)
  33. Domain Adaptation Bounds for Multiple Expert Systems Under Concept Drift
    G. Ditzler, G. Rosen, and R. Polikar
    IEEE/INNS International Joint Conference on Neural Networks, 2014. (travel award & best student paper)
  34. Incremental learning of new classes with unbalanced data
    G. Ditzler, G. Rosen, and R. Polikar
    IEEE/INNS International Joint Conference on Neural Networks, 2013.
  35. Discounted expert weighting for concept drift
    G. Ditzler, G. Rosen and R. Polikar
    IEEE International Symposium on Computational Intelligence in Dynamic and Uncertain Environments, 2013. (talk)
  36. Information theoretic feature selection for high dimensional metagenomic data
    G. Ditzler, R. Polikar, and G. Rosen
    IEEE International Workshop on Genomic Signal Processing and Statistics, 2012.
  37. A transductive learning algorithm for concept drift
    G. Ditzler, G. Rosen and R. Polikar
    IEEE/INNS International Joint Conference on Neural Networks, 2012.
  38. Determining significance in metagenomics
    G. Ditzler, R. Polikar and G. Rosen
    IEEE North Eastern Biomedical Engineering Conference, 2012.
  39. Forensic identification with environmental samples
    G. Ditzler, R. Polikar, and G. Rosen
    IEEE International Conference on Acoustic, Speech and Signal Processing, 2012.
  40. Semi-supervised learning in nonstationary environments
    G. Ditzler and R. Polikar
    IEEE/INNS International Joint Conference on Neural Networks, 2011. (student travel award)
  41. Hellinger distance based drift detection algorithm
    G. Ditzler and R. Polikar
    IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments, 2011.
  42. Fusion methods for boosting performance of speaker identification systems
    G. Ditzler, J. Ethridge, R. Polikar, and R. Ramachandran
    Asia Pacific Conference of Circuits and Systems, 2010.
  43. An incremental learning algorithm for nonstationary environments and imbalanced data
    G. Ditzler, R. Polikar, and N. V. Chawla
    International Conference on Pattern Recognition, 2010.
  44. Optimal \(\nu\)-SVM parameter estimation using multi-objective evolutionary algorithms
    J. Ethridge, G. Ditzler, and R. Polikar
    IEEE Congress on Evolutionary Computing, 2010.
  45. An ensemble-based incremental learning framework for concept drift and class imbalance
    G. Ditzler and R. Polikar
    IEEE/INNS International Joint Conference on Neural Networks, 2010.
  46. Incremental learning of new classes in unbalanced data: Learn++.UDNC
    G. Ditzler, M. Muhlbaier, and R. Polikar
    International Workshop on Multiple Classifier Systems, 2010.

Book Chapters

  1. Analysis Methods for Shotgun Metagenomics
    S. Woloszynek, Z. Zhao, G. Ditzler, J. R. Price, E. R. Reichenberger, Y. Lan, J. Chen, J. Earl, S. Keshani Langroodi, G. Ehrlich and G. Rosen
    Springer Theoretical and Applied Aspects of Systems Biology, 2018, pp. 71–112.
  2. Adaptive classifiers for nonstationary environments
    C. Alippi, G. Boracchi, G. Ditzler, R. Polikar, and M. Roveri
    Contemporary Issues in Systems, Science and Engineering, IEEE/Wiley Press Book Series, 2015.
  3. Variable Selection to Improve Classification of Metagenomes
    G. Ditzler, Y. Lan, J.-L. Bouchot, and G. Rosen
    In: Nelson K. (eds) Encyclopedia of Metagenomics. Springer, New York, NY, 2014.
  4. Advances in machine learning for processing and comparison of metagenomic data
    J.-L. Bouchot, W. Trimble, G. Ditzler, Y. Lan, S. Essinger, and G. Rosen
    In: Computational Systems Biology, 295-329, 2014

Technical Reports

  1. Review of Automatic Speech Recognition Methodologies
    G. Achour, O. Salunke, A. Payan, E. Harrison, C. Sahbani, G. Carannante, G. Ditzler, N. Bouaynaya
    United States. Department of Transportation. Federal Aviation Administration. William J. Hughes Technical Center, DOT/FAA/TC-23/47, 2023.

Patents

  1. Convolutional neural networks for pavement roughness assessment using calibration-free vehicle dynamics
    Hongki Jo, Jong-hyun Jeong, Gregory Ditzler
    US Patent App. 18/554,891, 2024