| 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 | 443 | 2013 |
| Learning a symbolic representation for multivariate time series classification MG Baydogan, G Runger Data Mining and Knowledge Discovery 29 (2), 400-422, 2015 | 210 | 2015 |
| Time series representation and similarity based on local autopatterns MG Baydogan, G Runger Data Mining and Knowledge Discovery 30 (2), 476-509, 2016 | 200 | 2016 |
| Autoregressive forests for multivariate time series modeling KS Tuncel, MG Baydogan Pattern recognition 73, 202-215, 2018 | 97 | 2018 |
| 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 | 71 | 2009 |
| Explainable boosted linear regression for time series forecasting I Ilic, B Görgülü, M Cevik, MG Baydoğan Pattern Recognition 120, 108144, 2021 | 60 | 2021 |
| 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 | 35 | 2017 |
| Multivariate time series classification datasets MG Baydogan https://drive.google.com/file/d/0ByJL28mvhOeaNVNaLU1fN3g2X2M/, 2015 | 32 | 2015 |
| 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 | 30 | 2015 |
| 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 | 22 | 2015 |
| The benefits of target relations: a comparison of multitask extensions and classifier chains E Adıyeke, MG Baydoğan Pattern Recognition 107, 107507, 2020 | 14 | 2020 |
| Bag Encoding Strategies in Multiple Instance Learning Problems EŞ Küçükaşcı, MG Baydoğan Information Sciences 467, 559 - 578, 2018 | 12 | 2018 |
| nTreeClus: a Tree-based Sequence Encoder for Clustering Categorical Series H Jahanshahi, MG Baydogan Neurocomputing 494, 224-241, 2022 | 9 | 2022 |
| A new feature-based time series classification method by using scale-space extrema T Altay, MG Baydoğan Engineering Science and Technology, an International Journal 24 (6), 1490-1497, 2021 | 8 | 2021 |
| Multivariate time series classification datasets (2015) MG Baydogan URL http://mustafabaydogan. com.[Accessed: 2020-02-05], 2020 | 8 | 2020 |
| Semi-supervised extensions of multi-task tree ensembles E Adıyeke, MG Baydoğan Pattern Recognition, 108393, 2022 | 7 | 2022 |
| An ensemble-based semi-supervised feature ranking for multi-target regression problems E Adıyeke, MG Baydoğan Pattern Recognition Letters 148, 36-42, 2021 | 7 | 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 | 7 | 2019 |
| SMT: Sparse multivariate tree H Deng, MG Baydogan, G Runger Statistical Analysis and Data Mining 7 (1), 53-69, 2014 | 6 | 2014 |
| Modeling Time Series Data for Supervised Learning MG Baydogan Arizona State University, 2012 | 6 | 2012 |
Robert K. AtkinsonArizona State UniversityVerified email at asu.edu
