Publications

Journals

Published:

  1. S. Colonnese, P. P. Markopoulos, G. Scarano, and D. A. Pados, “FFT Calculation of the L1-norm Principal Component of a Data Matrix,” Signal Processing (Elsevier), vol. 189, no. 108286, August 2021.

  2. D. G. Chachlakis, T. Zhou, F. Ahmad, P. P. Markopoulos, “Minimum Mean-Squared-Error Autocorrelation Processing in Coprime Arrays,” Digital Signal Processing (Elsevier), vol. 114, no. 103034, July 2021.

  3. D. G. Chachlakis, M. Dhanaraj, A. Prater-Bennette, P. P. Markopoulos, “Dynamic L1-norm Tucker Tensor Decomposition,” IEEE Journal on Selected Topics in Signal Processing, Special Issue on Tensor Decomposition for Signal Processing and Machine Learning, vol. 15, no. 3, pp. 587-602, April 2021.

  4. D. G. Chachlakis and P. P. Markopoulos, “Structured Autocorrelation Matrix Estimation for Coprime Arrays,” Signal Processing (Elsevier), vol. 183, no. 107987, June 2021.

  5. M. Sharma, M. Dhanaraj, D. G. Chachlakis, S. Karam, R. Ptucha, P. P. Markopoulos, E. Saber, “YOLOrs: Object Detection in Multimodal Remote Sensing Imagery,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 1497 - 1508, November 2020.

  6. H. Kamrani, A. Zoghadr Asli, P. P. Markopoulos M. Langberg, D. A. Pados, G. N. Karystinos, “Reduced-Rank L1-Norm Principal-Component Analysis with Performance Guarantees,” IEEE Trans. on Signal Processing, vol. 69, pp. 240 - 255, November 2020.

  7. S. A. Mamun, A. Ganguly, P. P. Markopoulos, M. Kwon, and A. Kwasinski, “NASCon: Network-Aware Server Consolidation for Server-Centric Wireless Datacenters,” Sustainable Computing: Informatics and Systems (Elsevier), vol. 29 (part A), no. 100452, March 2021.

  8. D. G. Chachlakis, P. P. Markopoulos, and A. Prater-Bennette, “L1-Norm Tucker Tensor Decomposition,” IEEE Access, vol. 7, pp. 178454 - 178465, November 2019.

  9. Y. Liang, P. P. Markopoulos, and E. Saber, “Spatial-Spectral Segmentation of Hyperspectral Images for Subpixel Target Detection,” SPIE Journal of Applied Remote Sensing, vol. 13, no. 3, pp. 036502:1-036502:16, July 2019.

  10. P. P. Markopoulos, N. Tsagkarakis, D. A. Pados, and G. N. Karystinos, “Realified L1-PCA for Direction-of-Arrival Estimation: Theory and Algorithms,” Eurasip Journal on Advances in Signal Processing, vol. 30, June 2019.

  11. P. P. Markopoulos, S. Zlotnikov, and F. Ahmad, “Adaptive Radar-Based Human Activity Recognition with L1-norm Linear Discriminant Analysis,” IEEE Journal of Electromagnetics, RF, and Microwaves in Medicine and Biology, vol. 3, no. 2, pp. 120 - 126, June 2019.

  12. P. P. Markopoulos, M. Dhanaraj, and A. Savakis, “Adaptive L1-Norm Principal-Component Analysis with Online Outlier Rejection,” IEEE Journal Selected Topics in Signal Processing, vol. 12, no. 6, pp. 1 - 13, December 2018.

  13. N. Tsagkarakis, P. P. Markopoulos, and D. A. Pados, “L1-Norm Principal-Component Analysis of Complex Data,” IEEE Transactions on Signal Processing, vol. 66, no. 12, pp. 3256 - 3267, June 2018.

  14. P. P. Markopoulos, D. G. Chachlakis, and E. E. Papalexakis, “The Exact Solution to Rank-1 L1-Norm TUCKER2 Decomposition,” IEEE Signal Processing Letters, vol. 25, no. 4, pp. 511-515, April 2018.

  15. P. P. Markopoulos and G. N. Karystinos, “Noncoherent Alamouti Phase-Shift Keying with Full-Rate Encoding and Polynomial-Complexity Maximum-Likelihood Decoding,” IEEE Transactions on Wireless Communications,” vol. 16, no. 10, pp. 6688-6697, July 2017.

  16. P. P. Markopoulos, S. Kundu, S. Chamadia, and D. A. Pados, “Efficient L1-Norm Principal-Component Analysis via Bit Flipping,” IEEE Transactions on Signal Processing, vol. 65, pp. 4252-4264, August 2017.

  17. P. P. Markopoulos, G. N. Karystinos, and D. A. Pados, “Optimal Algorithms for L1-Subspace Signal Processing,” IEEE Transactions on Signal Processing, vol. 62, pp. 5046-5058, October 2014.

  18. P. P. Markopoulos, S. Kundu, and D. A. Pados, “Small-Sample-Support Suppression of Interference to PN-Masked Data,” IEEE Transactions on Communications, vol. 61, pp. 2979-2987, July 2013.

  19. A. Bletsas, A. Vlachaki, E. Kampianakis, G. Sklivanitis, J. Kimionis, K. Tountas, M. Asteris, and P. P. Markopoulos, “Building a Low-Cost Digital Garden as a Telecom Lab Exercise,” IEEE Pervasive Computing, vol. 12, pp. 48-57, January 2013.

Submitted:

  1. M. Dhanaraj and P. P. Markopoulos, “On the Asymptotic Equivalence of L1-PCA and PCA for Elliptically Distributed Data,” submitted to IEEE Signal Processing Letters.

  2. M. Dhanaraj and P. P. Markopoulos, “Lightweight Convolutional Neural Networks via Multilinear Transformations,” submitted to IEEE Trans. on Neural Networks and Learning Systems.

  3. S. Colonnese, G. Scarano, M. Marra, P. P. Markopoulos, and D. A. Pados, “Joint Segmentation and L1-PCA of Time-Varying Data with Outliers,” submitted to Pattern Recognition (Elsevier).

Book Chapters

  1. D. G. Chachlakis, M. Dhanaraj, P. P. Markopoulos, A. Prater-Bennette, and I. Tomeo, "D-L1-Tucker: Dynamic and Robust Analysis of Tensor Data Based on Absolute Projection Maximization," to appear in Handbook on Dynamic Data Driven Application Systems (Vol. II).

  2. F. Ahmad and P. P. Markopoulos, "L1-Norm Principal Component and Discriminant Analyses of Micro-Doppler Signatures for Indoor Human Activity Recognition," in Micro-Doppler Radar and its Applications, F. Fioranelli, M Ritchie, A. Balleri and H. Griffiths (Eds.), IET Press, 2020.

  3. P. P. Markopoulos, S. Kundu, S. Chamadia, N. Tsagkarakis, and D. A. Pados, "Outlier-Resistant Data Processing with L1-norm Principal Component Analysis," in Advances in Principal Component Analysis: Research and Development, Ganesh R. Naik (Ed.), Springer, 2018.

Conference Papers

  1. M. Sharma, P. P. Markopoulos, E. Saber, M. S. Asif, and A. Prater-Bennette, "Convolutional Auto-Encoder with Tensor-Train Factorization," accepted to appear in Proc. International Conference on Computer Vision, (ICCV 2021), RLS-CV workshop.

  2. M. Mozaffari, P. P. Markopoulos, and A. Prater-Bennette, "Improved L1-Tucker via L1-Fitting," to appear in Proc. European Signal Processing Conference (EUSIPCO 2021), Dublin, Ireland, August 2021.

  3. M. Mozaffari and P. P. Markopoulos, "Robust Barron-Loss Tucker Tensor Decomposition," to appear in Proc. IEEE Asilomar Conference on Signals, Systems, and Computing (IEEE ACSSC), Pacific Grove, CA, November 2021.

  4. M. Sharma, P. P. Markopoulos, and E. Saber, "YOLOrs-LITE: A Lightweight CNN for Real-time Object Detection in Remote Sensing," to appear in Proc. IEEE International Geoscience and Remote Sensing Symposium (IEEE IGARSS), Brussels, Belgium, July 2021.

  5. D. G. Chachlakis and P. P. Markopoulos, “Novel Algorithms for Lp-quasi-norm Principal-Component Analysis,” Proc. European Signal Processing Conference (EUSIPCO 2020), Amsterdam, Netherlands, January 2021.

  6. S. A. Mamun, A. Ganguly, P. P. Markopoulos, A. Kwasinski, and M. Kwon, “What Can Ail Thee: New and Old Security Vulnerabilities of Wireless Datacenters,” to appear in Proc. IEEE Global Communications Conference (IEEE GLOBECOM), Taipei, Taiwan, December 2020.

  7. G. Sklivanitis, P. P. Markopoulos, D. A. Pados, and R. Diamant, “Robust Graph Localization for Underwater Acoustic Networks,” to appear in Proc. IEEE Underwater Communications and Networking Conference (IEEE UCOMMS), Lerici, Italy, December 2020.

  8. Y. Tsitsikas, D. G. Chachlakis, E. Papalexakis, P. P. Markopoulos, “L1-Norm RESCAL Decomposition,” in Proc. IEEE Asilomar Conference on Signals, Systems, and Computing (IEEE ACSSC), Pacific Grove, CA, November 2020.

  9. D. Chachlakis, A. Prater-Bennette, and P. P. Markopoulos, “L1-Norm Higher-order Orthogonal Iterations for Robust Tensor Analysis,” in Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing (IEEE ICASSP), Barcelona, Spain, May 2020.

  10. M. Dhanaraj, M. Sharma, T. Sarkar, S. Karnam, D. G. Chachlakis, R. Ptucha, P. P. Markopoulos, and E. Saber, “Vehicle Detection from Multi-modal Aerial Imagery Using YOLOv3 with Mid-level Fusion​,” in Proc. SPIE Defense and Commercial Sensing (SPIE DCS), Anaheim, CA, April 2020.

  11. K. Tountas, D. Chachlakis, P. P. Markopoulos, D. A. Pados, “Iteratively Re-weighted L1-norm PCA of Tensor Data,” in Proc. IEEE Asilomar Conference on Signals, Systems, and Computers (IEEE ACSSC), Pacific Grove, CA, October 2019.

  12. D. G. Chachlakis and P. P. Markopoulos, Combinatorial search for the Lp-norm principal component of a matrix, in Proc. IEEE Asilomar Conference on Signals, Systems, and Computers (IEEE ACSSC), Pacific Grove, CA, October 2019.

  13. S. Ashraf Mamun, A. Ganguly, M. Kwon, A. Kwasinski, P. P. Markopoulos, “Network-Aware Server Consolidation for Wireless Data Centers,” in Proc. 10th International Conference of Networks of the Future, Rome, Italy, October 2019.

  14. D. Chachlakis, Y. Tsitsikas, E. Papalexakis, and P. P. Markopoulos, “Robust Multi-Relational Learning with Absolute Projection RESCAL,” in Proc. IEEE Global Conference on Information Processing (IEEE GlobalSIP), Ottawa, Canada, November 2019.

  15. M. Dhanaraj and P. P. Markopoulos, "Stochastic Principal Component Analysis via Mean Absolute Projection Maximization," in Proceedings IEEE Global Conference on Signal and Information Processing (IEEE GlobalSIP 2019), Ottawa, Canada, November 2019.

  16. Giovanna Orrù, Tiziana Cattai, Stefania Colonnese, Gaetano Scarano, Fabrizio De Vico Fallani, P. P. Markopoulos, and Dimitris Pados, “Deep L1-PCA of Time-Variant Data with Application to Brain Connectivity Measurements,” in Proc. 27th European Signal Processing Conference (EUSIPCO), A Coruña, Spain, September 2019.

  17. D. G. Chachlakis, M. Dhanaraj, P. P. Markopoulos, and A. Prater-Bennette, “Options for Multimodal Classification Based on L1-Tucker Decomposition,” in Proc. 2019 SPIE Defense and Commercial Sensing (SPIE DCS) Baltimore, MD, April 2019.

  18. S. Zlotnikov, P. P. Markopoulos, and F. Ahmad, “Incremental L1-Norm Linear Discriminant Analysis for Indoor Human Activity Classification,” in Proc. 2019 IEEE Radar Conference (IEEE RADARCONF), Boston, MA, April 2019.

  19. P. P. Markopoulos, D. G. Chachlakis, A. Prater-Bennette, “L1-Norm Higher-Order Singular-Value Decomposition,” in Proc. IEEE Global Conference on Signal and Information Processing (IEEE GlobalSIP), Anaheim, CA, November 2018, pp. 1353-1357.

  20. K. Bichave, O. Brewer, M. Gusinov, P. P. Markopoulos, and I. Puchades, “Gait Recognition Based on Tensor Analysis of Acceleration Data From Wearable Sensors,” in Proc. IEEE Western New York Signal and Image Processing Workshop (IEEE WNYSIPW), Rochester, NY, October 2018, pp. 1-5. Runner-up for Best Poster Award at IEEE WNYISPW 2018.

  21. M. Dhanaraj, D. G. Chachlakis, and P. P. Markopoulos, “Incremental Complex L1-PCA for Direction-of-Arrival Estimation,” in Proc. IEEE Western New York Signal and Image Processing Workshop (IEEE WNYSIPW), Rochester, NY, October 2018, pp. 1-5.

  22. A. Gannon, G. Sklivanitis, P. P. Markopoulos, D. A. Pados, and S. N. Batalama, “Semi-Blind Signal Recovery in Impulsive Noise with L1-Norm PCA,” in Proc. IEEE Asilomar Conference on Signals, Systems, and Computers (IEEE ACSSC), Pacific Grove, CA, October 2018, pp. 477-481.

  23. M. Dhanaraj and P. P. Markopoulos, “Novel Algorithm for Incremental L1-Norm Principal-Component Analysis,” in Proc. IEEE/EURASIP European Signal Processing Conference (EUSIPCO), Rome, Italy, September 2018, 2020-2024.

  24. P. P. Markopoulos and F. Ahmad, “Robust Radar-Based Human Motion Recognition with L1-Norm Linear Discriminant Analysis,” in Proc. IEEE International Microwave Biomedical Conference (IEEE IMBioC), Philadelphia, PA, June 2018, pp. 145-147.

  25. D. G. Chachlakis, P. P. Markopoulos, and F. Ahmad, “MMSE-Based Autocorrelation Sampling for Coprime Arrays,” in Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing (IEEE ICASSP), Calgary, Canada, April 2018, pp. 3474-3478.

  26. D. G. Chachlakis and P. P. Markopoulos, “Novel Algorithms for Exact and Efficient L1-Norm-Based TUCKER2 Decomposition,” in Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing (IEEE ICASSP), Calgary, Canada, April 2018, 6294-6298.

  27. D. G. Chachlakis and P. P. Markopoulos, “Robust Decomposition of 3-Way Tensors Based on L1-Norm,” in Proc. SPIE Defense and Commercial Sensing (SPIE DCS), Orlando, FL, April 2018, p. 1065807.

  28. S. Zlotnikov, P. Somaru, P. P. Markopoulos, and F. Ahmad, “A Linear Discriminative Analysis Based Fall Motion Detector Using Radar,” in Proc. SPIE Defense and Commercial Sensing (SPIE DCS), Orlando, FL, April 2018, p. 106580D.

  29. D. G. Chachlakis, P. P. Markopoulos, and F. Ahmad, “The Mean-Squared-Error of Autocorrelation Sampling in Coprime Arrays,” in Proc. IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (IEEE CAMSAP), Curacao, Dutch Antilles, December 2017, pp. 1-5.

  30. P. P. Markopoulos and F. Ahmad, “Indoor Human Motion Classification by L1-Norm Subspaces of Micro-Doppler Signatures,” in Proc. IEEE Radar Conference (IEEE RADARCONF), Seattle, WA, May 2017, pp. 1807-1810.

  31. P. P. Markopoulos, D. A. Pados, G. N. Karystinos, and M. Langberg, “L1-Norm Principal-Component Analysis in L2-Norm-Reduced-Rank Data Subspaces,” in Proc. SPIE Defense and Commercial Sensing (SPIE DCS), Anaheim, CA, April 2017, p. 1021104.

  32. D. G. Chachlakis, P. P. Markopoulos, R. J. Muchhala, and A. Savakis, “Visual Tracking with L1-Grassmann Manifold Modeling,” in Proc. SPIE Defense and Commercial Sensing (SPIE DCS), Anaheim, CA, April 2017, p. 1021102.

  33. G. Sklivanitis, P. P. Markopoulos, S. Batalama, and D. A. Pados, “Adaptive Sparse-Binary Waveform Design for All-Spectrum Channelization,” in Proc. SPIE Defense and Commercial Sensing (SPIE DCS), Anaheim, CA, April 2017, p. 102110B. Student Travel Grant.

  34. P. P. Markopoulos, “Linear Discriminant Analysis with Few Training Data,” in Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing (IEEE ICASSP), New Orleans, LA, March 2017, pp. 4626-4629

  35. G. Sklivanitis, P. P. Markopoulos, S. Batalama, and D. A. Pados, “Sparse Waveform Design for All-Spectrum Channelization,” in Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing (IEEE ICASSP), New Orleans, LA, March 2017, pp. 3764-3768.

  36. N. Tsagkarakis, P. P. Markopoulos, and D. A. Pados, “On the L1-norm Approximation of a Matrix by Another of Lower Rank,” in Proc. IEEE International Conference on Machine Learning and Applications (IEEE ICMLA), Anaheim, CA, December 2016, pp. 768-773.

  37. P. P. Markopoulos, S. Kundu, S. Chamadia, and D. A. Pados, “L1-Norm Principal-Component Analysis via Bit Flipping,” in Proc. IEEE International Conference on Machine Learning and Applications (IEEE ICMLA), Anaheim, CA, December 2016, pp. 326-332.

  38. P. P. Markopoulos, N. Tsagkarakis, D. A. Pados, and G. N. Karystinos, “Direction-of-Arrival Estimation from L1-Norm Principal Components,” in Proc. IEEE International Symposium on Phased Array Systems and Technology (IEEE PAST), Boston, MA, October 2016, pp. 1-6.

  39. Y. Liang, P. P. Markopoulos, and E. Saber, “Subpixel Target Detection in Hyperspectral Images with Local Matched Filtering in SLIC Superpixels,” in Proc. IEEE Workshop on Hyperspectral Image and Signal Processing: Evolutions in Remote Sensing (IEEE WHISPERS), Los Angeles, CA, August 2016, pp. 1-5.

  40. P. P. Markopoulos, “Reduced-Rank Filtering on L1-Norm Subspaces,” in Proc. IEEE Sensor Array and Multichannel Signal Processing Workshop (IEEE SAM), Rio de Janeiro, Brazil, July 2016, pp. 1-5.

  41. Y. Liang, P. P. Markopoulos, and E. Saber, “Subpixel Target Detection in Hyperspectral Images from Superpixel Background Statistics,” in Proc. IEEE International Geoscience and Remote Sensing Symposium (IEEE IGARSS), Beijing, China, July 2016, pp. 7018-7021.

  42. P. P. Markopoulos, S. Kundu, and D. A. Pados, “L1-Fusion: Robust Linear-Time Image Recovery from Few Severely Corrupted Copies,” in Proc. IEEE International Conference on Image Processing (IEEE ICIP), Quebec City, Canada, September 2015, pp. 1225-1229.

  43. N. Tsagkarakis, P. P. Markopoulos, and D. A. Pados, “Direction Finding by Complex L1-Principal Component Analysis,” in Proc. IEEE International Workshop on Signal Processing Advances in Wireless Communications (IEEE SPAWC), Stockholm, Sweden, June 2015, pp. 475-479.

  44. P. P. Markopoulos, N. Tsagkarakis, D. A. Pados, and G. N. Karystinos, “Direction Finding with L1-Norm Subspaces,” in Proc. SPIE Defense, Security, and Sensing (SPIE DSS), Baltimore, MD, May 2014, vol. 9109, pp. 0J1-0J11. Student Travel Grant.

  45. S. Kundu, P. P. Markopoulos, and D. A. Pados, “Fast Computation of the L1-Principal Component of Real-Valued Data,” in Proc. IEEE International Conference on Acoustics, Speech, and SignalProcessing (IEEE ICASSP), Florence, Italy, May 2014, pp. 8028-8032.

  46. P. P. Markopoulos, G. N. Karystinos, and D. A. Pados, “Some Options for L1-Subspace Signal Processing,” in Proc. IEEE International Symposium on Wireless Communication Systems (IEEE ISWCS 2013), Ilmenau, Germany, August 2013, pp. 622-626. IEEE ISWCS 2013 Best Paper Award.

  47. P. P. Markopoulos and G. N. Karystinos, “Novel Full-Rate Noncoherent Alamouti Encoding that Allows Polynomial-Complexity Optimal Decoding,” in Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing (IEEE ICASSP) , Vancouver, Canada, May 2013, pp. 5075-5079.

  48. P. P. Markopoulos, S. Kundu, and D. A. Pados, “Short-Data-Record Filtering of PN-Masked Data,” in Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing (IEEE ICASSP), Vancouver, Canada, May 2013, pp. 4559-4563.

  49. A. Bletsas, A. Vlachaki, E. Kampianakis, G. Sklivanitis, J. Kimionis, K. Tountas, M. Asteris, and P. P. Markopoulos, “Towards Precision Agriculture: Building a Soil Wetness Multi-Hop WSN from First Principles,” in Proc. International Workshop in Sensing Technologies in Architecture, Forestry and Environment (ECOSENSE) Belgrade, Serbia, April 2011, pp. 1-4.

Invited Talks

  1. P. P. Markopoulos, “Tensor-Based Parametrization of Object Detection CNNs and Application to Aerial Imagery,” invited speaker, 6th Annual Intelligence Community Academic Research Symposium, National Academies of Science, Engineering, and Medicine, September 2021.

  2. P. P. Markopoulos, “Recent Advances in Tensor Subspace Analysis Based on Absolute Projections,” invited speaker, Joint EME and CE Grad Seminar, RIT, May 2021.

  3. P. P. Markopoulos, Dynamic and Robust Tensor Analysis Based on Absolute Projections, invited speaker, IEEE Mohawk Valley Section, Dec. 2020 (remotely).

  4. P. P. Markopoulos, Recent Advances in Tensor Subspace Analysis Based on Absolute Projections, invited speaker, CIS Weekly Seminar, Chester F. Carlson Center for Imaging Science, RIT, Nov. 2020 (remotely).

  5. P. P. Markopoulos, Advances in Tensor Subspace Analysis Based on Absolute Projections, invited speaker, Applied Math Seminar, Department of Mathematics, Syracuse University, Oct. 2020 (remotely).

  6. P. P. Markopoulos, Improving CNNs Towards Real-Time Multi-Modal Object Detection in Remote Sensing Imagery, invited speaker, 6th Annual Intelligence Community Academic Research Symposium, Sept. 2020 (remotely).

  7. P. P. Markopoulos, Improving CNNs Towards Real-Time Multi-Modal Object Detection in Remote Sensing Imagery, invited speaker, 2020 Summer School on Data Science, Technical University of Crete (TUC), Chania, Greece, Aug. 2020 (remotely).

  8. P. P. Markopoulos, New methods for corruption-resistant L1-norm tensor decomposition, invited speaker, SIAM IS20, Tensor Methods for Image Processing Mini-symposium, Toronto, Canada, Jul. 2020 (remotely).

  9. P. P. Markopoulos, Improving CNNs Towards Real-Time Multi-Modal Object Detection in Remote Sensing Imagery, invited speaker, NGA Webinar, Jul. 2020 (remotely).

  10. P. P. Markopoulos, L1-Tucker: A New Paradigm for Robust Tensor Data Analysis, invited speaker, ECE Dept., Temple University, Philadelphia PA, Apr. 2020 (remotely).

  11. P. P. Markopoulos, L1-norm principal component analysis of matrices and tensors: Algorithms, theory, and some applications, invited keynote speaker, International Conference on Computer Vision (ICCV), Robust Subspace Learning and Applications in Computer Vision Workshop (RSL-CV), Oct. 2019, Seoul, Korea.

  12. P. P. Markopoulos, Matrix and tensor analysis based on absolute projections, invited speaker, Dept. of ECE, University of California San Diego, San Diego, CA, Oct. 2019.

  13. P. P. Markopoulos, L1-norm principal component analysis of multi-modal data, invited speaker, 2018 Summer School, Technical University of Crete (TUC), Chania, Greece, Jul. 2018.

  14. P. P. Markopoulos, Outlier-resistant PCA: Algorithms and applications, invited speaker, U.S. Air Force Research Lab (AFRL), Rome, NY, Jun. 2018.

  15. P. P. Markopoulos, Algorithmic advances in L1-norm tensor analysis, invited speaker, The Institute for Sensing and Embedded Network Systems Engineering (I-SENSE), Florida Atlantic University, FL, May 2018.

  16. P. P. Markopoulos, New tensor methods for robust signal processing, speaker at MSEE Graduate Seminar, RIT, Apr. 2018.

  17. P. P. Markopoulos, Outlier-resistant L1-norm analysis of data matrices and tensors: Theory and algorithmic tools, invited speaker, Spring Move78/AI and Cognitive Technologies Speaker Series, Rochester Institute of Technology, Jan., 2018.

  18. P. P. Markopoulos, L1-norm Principal-Component Analysis: New options for outlier-resistant signal processing and machine learning, invited speaker, University of Rochester (IEEE Rochester Section, AES/COMSOC Meeting), Rochester NY, Nov. 2016.

  19. P. P. Markopoulos, A new paradigm for robust signal processing and data analysis based on absolute projections, invited talk, Department of Electrical and Microelectronic Engineering, Rochester Institute of Technology, Rochester, NY, Mar. 2015.

  20. P. P. Markopoulos, Questions and some recent answers on L1-principal component analysis, invited speaker, Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, Oct. 2014.

  21. P. P. Markopoulos, L1-norm PCA: A new paradigm in machine learning and signal processing, presenter, IEEE North American School of Information Theory (NASIT '14), Toronto, Canada, Jun. 2014.