| A bag-of-features framework to classify time series M Baydogan, G Runger, E Tuv IEEE Transactions on Pattern Analysis and Machine Intelligence 35 (11), 2796 …, 2013 | 294 | 2013 |
| Learning a symbolic representation for multivariate time series classification MG Baydogan, G Runger Data Mining and Knowledge Discovery 29 (2), 400-422, 2015 | 138 | 2015 |
| Time series representation and similarity based on local autopatterns MG Baydogan, G Runger Data Mining and Knowledge Discovery 30 (2), 476-509, 2016 | 128 | 2016 |
| Toward development of adaptive service-based software systems SS Yau, N Ye, HS Sarjoughian, D Huang, A Roontiva, M Baydogan, ... IEEE transactions on services computing 2 (3), 247-260, 2009 | 68 | 2009 |
| Autoregressive forests for multivariate time series modeling KS Tuncel, MG Baydogan Pattern recognition 73, 202-215, 2018 | 56 | 2018 |
| A Transfer Learning Approach for Predictive Modeling of Degenerate Biological Systems N Zou, Y Zhu, J Zhu, M Baydogan, W Wang, J Li Technometrics 57 (3), 362-373, 2015 | 22 | 2015 |
| Affect measurement: A roadmap through approaches, technologies, and data analysis J Gonzalez-Sanchez, M Baydogan, ME Chavez-Echeagaray, RK Atkinson, ... Emotions and affect in human factors and human-computer interaction, 255-288, 2017 | 18 | 2017 |
| Metabolic connectivity as index of verbal working memory N Zou, G Chetelat, MG Baydogan, J Li, FU Fischer, D Titov, J Dukart, ... Journal of Cerebral Blood Flow & Metabolism 35 (7), 1122-1126, 2015 | 17 | 2015 |
| Multivariate time series classification datasets MG Baydogan | 11 | 2019 |
| Models of dynamic relations among service activities, system state and service quality on computer and network systems N Ye, S Yan, D Huang, M Baydogan, BM Aranda, A Roontiva, P Hurley Information, Knowledge, Systems Management 9 (2), 99-116, 2010 | 6 | 2010 |
| The benefits of target relations: A comparison of multitask extensions and classifier chains E Adıyeke, MG Baydoğan Pattern Recognition 107, 107507, 2020 | 5 | 2020 |
| Modeling Time Series Data for Supervised Learning MG Baydogan Arizona State University, 2012 | 5 | 2012 |
| Bag Encoding Strategies in Multiple Instance Learning Problems EŞ Küçükaşcı, MG Baydoğan Information Sciences 467, 559 - 578, 2018 | 3 | 2018 |
| Adaptive Advertisement Recommender Systems for Digital Signage S Addicam, S Balkan, M Baydogan 2015 Americas Conference on Information Systems, 2015 | 3 | 2015 |
| Pull-based milk-run distribution system design for a firm producing diesel injectors (Turkish: Dizel Enjektör Üretimi Yapan Bir Şirket İçin Fabrika İçi Çekme Esaslı Tekrarlı … AT AH Akıllıoğlu, MG Baydoğan, Y Bolatlı, D Canbaz, A Halıcı, Ö Sezgin, NE ... Ind Eng J (Turkish: Endüstri Mühendisliği Dergisi) 17 (3), 2-15, 2006 | 3 | 2006 |
| SMT: Sparse multivariate tree H Deng, MG Baydogan, G Runger Statistical Analysis and Data Mining 7 (1), 53-69, 2014 | 2 | 2014 |
| Affect Recognition in Learning Scenarios: Matching Facial-and BCI-Based Values J Gonzalez-Sanchez, ME Chavez-Echeagaray, L Lin, M Baydogan, ... 13th IEEE International Conference on Advanced Learning Technologies (ICALT'13), 2013 | 2 | 2013 |
| Explainable boosted linear regression for time series forecasting I Ilic, B Görgülü, M Cevik, MG Baydoğan Pattern Recognition 120, 108144, 2021 | 1 | 2021 |
| Randomized Trees for Time Series Representation and Similarity B Görgülü, MG Baydoğan Pattern Recognition, 108097, 2021 | 1 | 2021 |
| Estimation of Influence Distance of Bus Stops Using Bus GPS Data and Bus Stop Properties I Gokasar, Y Cetinel, MG Baydogan IEEE Transactions on Intelligent Transportation Systems 20 (12), 4635-4642, 2019 | 1 | 2019 |
Hessam S. SarjoughianAssociate Professor of Computer Science & Computer Engineering, Arizona State UniversityVerified email at asu.edu
