Publications

arXiv

  1. PACOL: Poisoning Attacks Against Continual Learners. H. Li and G. Ditzler. arXiv:2311.10919, 2023. arXiv

  2. Sleep Stage Classification with Learning from Evolving Datasets. H. Li, X. Chen, W. Killmore, S. Quan, G. Ditzler, P. Chang, J. Roveda, and A. Li. techrxiv.23730546.v1, 2023. TechRxiv

  3. A Maximum Log-Likelihood Method for Imbalanced Few-Shot Learning Tasks. S. Hess and G. Ditzler. arXiv:2211.14668, 2022. arXiv

  4. Edge-Guided Occlusion Fading Reduction for a Light-Weighted Self-Supervised Monocular Depth Estimation. K.-S. Peng, G. Ditzler, and J. Rozenblit. arXiv:1911.11705, 2019. arXiv

Journal Papers

  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. Link

  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. Link | arXiv

  3. ProtoShotXAI: Using Prototypical Few-Shot Architecture for Explainable AI. S. Hess and G. Ditzler. Journal of Machine Learning Research, vol. 24, no. 325, pp. 1-49, 2023. Link

  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. Link | arXiv

  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. Link

  6. Attack Transferability Against Information-Theoretic Feature Selection. S. Gupta, R. Golota, and G. Ditzler. IEEE Access, vol. 9, pp. 115885-115894, 2021. Link

  7. Data Poisoning Against Information-Theoretic Feature Selection. H. Liu and G. Ditzler. Information Sciences, vol. 573, pp. 396-411, 2021. Link

  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. Link

  9. Learning What We Don't Care About: Regularization with Sacrificial Functions. G. Ditzler, S. Miller, and J. Rozenblit. Information Sciences, vol. 496, pp. 198-211, 2019. Link

  10. A Semi-Parallel Framework for Greedy Information-Theoretic Feature Selection. H. Liu and G. Ditzler. Information Sciences, vol. 492, pp. 13-28, 2019. Link

  11. Approximate Kernel Reconstruction for Time-Varying Networks. G. Ditzler, N. Bouaynaya, R. Shterenberg, and H. M. Fathallah-Shaykh. BMC BioData Mining, vol. 12, no. 9, 2019. Link

  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, vol. 66, no. 1, pp. 561-570, 2019. Link

  13. Weight Normalization with Spiking Neural Networks. Z. Liang, D. Schwartz, G. Ditzler, and O. Ozan Koyluoglu. Neural Networks, vol. 108, pp. 365-378, 2018. Link

  14. AKRON: An Algorithm for Approximating Sparse Kernel Reconstruction. G. Ditzler, N. Bouaynaya, and R. Shterenberg. Signal Processing, vol. 144, pp. 265-270, 2018. Link

  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, vol. 29, no. 9, pp. 4504-4509, 2018. Link

  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, vol. 29, no. 6, pp. 2530-2544, 2018. Link

  17. Fizzy: Feature Selection for Metagenomics. G. Ditzler, J. Calvin Morrison, Y. Lan, and G. Rosen. BMC Bioinformatics, vol. 16, no. 358, 2015. Link

  18. Multi-Layer and Recursive Neural Networks for Metagenomic Classification. G. Ditzler, R. Polikar, and G. Rosen. IEEE Transactions on Nanobioscience, vol. 14, no. 6, pp. 608-616, 2015. Link

  19. Adaptive Strategies for Learning in Nonstationary Environments: A Survey. G. Ditzler, M. Roveri, C. Alippi, and R. Polikar. IEEE Computational Intelligence Magazine, vol. 10, no. 4, pp. 12-25, 2015. Link

  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, vol. 26, no. 4, pp. 880-886, 2015. Link

  21. Incremental Learning of Concept Drift from Streaming Imbalanced Data. G. Ditzler and R. Polikar. IEEE Transactions on Knowledge & Data Engineering, vol. 25, no. 10, pp. 2283-2301, 2013. Link

Conference Papers

  1. A Curriculum Learning Framework to Boost Object Detection on Unmanned Aerial Objects. E. Aslan, K. Naddeo, T. Bouhsine, R. Polikar, and G. Ditzler. IEEE Symposium on Computational Intelligence in Security, Defence and Biometrics, 2025. Link

  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. Link | 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, Synthetic Data for Artificial Intelligence and Machine Learning, 2023. Link | Talk

  4. On Reducing Adversarial Vulnerability with Data Dependent Stochastic Resonance. D. Schwartz and G. Ditzler. IEEE Symposium Series on Computational Intelligence, 2022. Link | Talk

  5. Application of Adversarial Machine Learning in Protocol and Modulation Misclassification. M. Krunz, W. Zhang, and G. Ditzler. SPIE Proceedings, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications IV, 2022. Link | 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. Link

  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. Link

  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. Link

  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. Link

  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. Link

  11. Bolstering Adversarial Robustness with Latent Disparity Regularization. D. Schwartz and G. Ditzler. IEEE/INNS International Joint Conference on Neural Networks, 2021. Link

  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. Link | 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. Link

  14. Bypassing Temporal Dependency in Adversarial Audio Examples. H. Liu and G. Ditzler. IEEE Symposium Series on Computational Intelligence, 2020. Link | Talk

  15. Detecting Adversarial Audio via Activation Quantization Error. H. Liu and G. Ditzler. IEEE/INNS International Joint Conference on Neural Networks, 2020. Link | 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. Link

  17. Poisoning mRMR with Adversarial Data. H. Liu and G. Ditzler. IEEE International Conference on Acoustics, Speech and Signal Processing, 2019. Link

  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. Link

  19. The Impact of an Adversary in a Language Model. Z. Liang and G. Ditzler. IEEE Symposium Series on Computational Intelligence, 2018. Link | 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. Link

  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. Link

  22. Fine Tuning Lasso in an Adversarial Environment Against Gradient Attacks. G. Ditzler and A. Prater. IEEE Symposium Series on Computational Intelligence, 2017. Link | 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. Link

  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. Link

  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. Link

  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. Link

  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. Link

  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. Link

  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. Link

  30. A Study of Incremental Spectral Meta-Learning for Nonstationary Environments. G. Ditzler. IEEE/INNS International Joint Conference on Neural Networks, 2016. Link | 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. Link | 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 presentation and travel award. Link

  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. Link

  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. Link

  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. Link | 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. Link

  37. A Transductive Learning Algorithm for Concept Drift. G. Ditzler, G. Rosen, and R. Polikar. IEEE/INNS International Joint Conference on Neural Networks, 2012. Link

  38. Determining Significance in Metagenomics. G. Ditzler, R. Polikar, and G. Rosen. IEEE North Eastern Biomedical Engineering Conference, 2012. Link

  39. Forensic Identification with Environmental Samples. G. Ditzler, R. Polikar, and G. Rosen. IEEE International Conference on Acoustics, Speech and Signal Processing, 2012. Link

  40. Semi-Supervised Learning in Nonstationary Environments. G. Ditzler and R. Polikar. IEEE/INNS International Joint Conference on Neural Networks, 2011. Student travel award. Link

  41. Hellinger Distance Based Drift Detection Algorithm. G. Ditzler and R. Polikar. IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments, 2011. Link

  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. Link

  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. Link

  44. Optimal v-SVM Parameter Estimation using Multi-Objective Evolutionary Algorithms. J. Ethridge, G. Ditzler, and R. Polikar. IEEE Congress on Evolutionary Computing, 2010. Link

  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. Link

  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. Link

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, pp. 71-112, 2018. Link

  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. Link

  3. Variable Selection to Improve Classification of Metagenomes. G. Ditzler, Y. Lan, J.-L. Bouchot, and G. Rosen. Encyclopedia of Metagenomics, Springer, 2014. Link

  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. Computational Systems Biology, pp. 295-329, 2014. Link

Technical Reports

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

Patents

  1. Convolutional Neural Networks for Pavement Roughness Assessment using Calibration-Free Vehicle Dynamics. H. Jo, J.-H. Jeong, and G. Ditzler. US Patent App. 18/554,891, 2024.