Deep Learning for RF Fingerprinting: A Massive Experimental Study T Jian, BC Rendon, E Ojuba, N Soltani, Z Wang, K Sankhe, A Gritsenko, ... IEEE Internet of Things Magazine 3 (1), 50-57, 2020 | 197 | 2020 |
Finding a ‘New’Needle in the Haystack: Unseen Radio Detection in Large Populations Using Deep Learning A Gritsenko, Z Wang, T Jian, J Dy, K Chowdhury, S Ioannidis 2019 IEEE International Symposium on Dynamic Spectrum Access Networks …, 2019 | 53 | 2019 |
Statistical Inference on the Number of Cycles in Brain Networks MK Chung, SG Huang, A Gritsenko, L Shen, H Lee 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019 …, 2019 | 23 | 2019 |
Open-world class discovery with kernel networks Z Wang, B Salehi, A Gritsenko, K Chowdhury, S Ioannidis, J Dy 2020 IEEE International Conference on Data Mining (ICDM), 631-640, 2020 | 22 | 2020 |
Embedded spectral descriptors: learning the point-wise correspondence metric via Siamese neural networks Z Sun, Y He, A Gritsenko, A Lendasse, S Baek Journal of Computational Design and Engineering 7 (1), 18-29, 2020 | 17 | 2020 |
MAC ID Spoofing-Resistant Radio Fingerprinting T Jian, BC Rendon, A Gritsenko, J Dy, K Chowdhury, S Ioannidis 2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP …, 2019 | 17 | 2019 |
Decomposition Analysis and Machine Learning in a Workflow-forecast Approach to the Task Scheduling Problem for High-Loaded Distributed Systems AV Gritsenko, NG Demurchev, VV Kopytov, AO Shulgin Modern Applied Science 9 (5), 38-49, 2015 | 17 | 2015 |
Deep spectral descriptors: learning the point-wise correspondence metric via Siamese deep neural networks Z Sun, Y He, A Gritsenko, A Lendasse, S Baek arXiv preprint arXiv:1710.06368 2, 2017 | 16 | 2017 |
Extreme Learning Machines for Multiclass Classification: Refining Predictions with Gaussian Mixture Models E Eirola, A Gritsenko, A Akusok, KM Björk, Y Miche, D Sovilj, R Nian, B He, ... International Work-Conference on Artificial Neural Networks, 153-164, 2015 | 14 | 2015 |
Deformable surface registration with extreme learning machines A Gritsenko, Z Sun, S Baek, Y Miche, R Hu, A Lendasse Proceedings of ELM-2017, 304-316, 2019 | 8 | 2019 |
Graph transfer learning A Gritsenko, K Shayestehfard, Y Guo, A Moharrer, J Dy, S Ioannidis Knowledge and Information Systems 65 (4), 1627-1656, 2023 | 7 | 2023 |
Adding Reliability to ELM Forecasts by Confidence Intervals A Akusok, A Gritsenko, Y Miche, KM Björk, R Nian, P Lauren, A Lendasse Neurocomputing 219, 232-241, 2017 | 7 | 2017 |
Topological brain network distances MK Chung, H Lee, A Gritsenko, A DiChristofano, D Pluta, H Ombao, ... arXiv preprint arXiv:1809.03878, 2018 | 5 | 2018 |
Advanced query strategies for Active Learning with Extreme Learning Machines. A Akusok, E Eirola, Y Miche, A Gritsenko, A Lendasse ESANN, 2017 | 5 | 2017 |
Probabilistic Methods for Multiclass Classification Problems A Gritsenko, E Eirola, D Schupp, E Ratner, A Lendasse Proceedings of ELM-2015 Volume 2, 385-397, 2016 | 5 | 2016 |
A modern approach for constructing scheduling and resource providing algorithms based on the prediction of the workflow AV Gritsenko Applied and Fundamental Studies, 144-147, 2013 | 5 | 2013 |
Prediction of DRMS workload by identification of patterns in job submission processes A Gritsenko Journal of International Scientific Publications: Materials, Methods and …, 2012 | 5 | 2012 |
Twin Classification in Resting-State Brain Connectivity A Gritsenko, M Lindquist, MK Chung 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 1391-1394, 2020 | 4 | 2020 |
Circular Pearson Correlation Using Cosine Series Expansion SG Huang, A Gritsenko, MA Lindquist, MK Chung 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019 …, 2019 | 4 | 2019 |
Combined Nonlinear Visualization and Classification: ELMVIS++ C A Gritsenko, A Akusok, Y Miche, KM Björk, S Baek, A Lendasse Neural Networks (IJCNN), 2016 International Joint Conference on, 2617-2624, 2016 | 4 | 2016 |