Time series classification from scratch with deep neural networks: A strong baseline Z Wang, W Yan, T Oates 2017 International joint conference on neural networks (IJCNN), 1578-1585, 2017 | 2126 | 2017 |
Imaging time-series to improve classification and imputation Z Wang, T Oates arXiv preprint arXiv:1506.00327, 2015 | 851 | 2015 |
Encoding time series as images for visual inspection and classification using tiled convolutional neural networks Z Wang, T Oates Workshops at the twenty-ninth AAAI conference on artificial intelligence, 2015 | 626 | 2015 |
Efficient progressive sampling F Provost, D Jensen, T Oates Proceedings of the fifth ACM SIGKDD international conference on Knowledge …, 1999 | 539 | 1999 |
Clustering time series with hidden markov models and dynamic time warping T Oates, L Firoiu, PR Cohen Proceedings of the IJCAI-99 workshop on neural, symbolic and reinforcement …, 1999 | 283 | 1999 |
Detecting spam blogs: A machine learning approach P Kolari, A Java, T Finin, T Oates, A Joshi Proceedings of the national conference on artificial intelligence 21 (2), 1351, 2006 | 232 | 2006 |
The effects of training set size on decision tree complexity T Oates, D Jensen Sixth International Workshop on Artificial Intelligence and Statistics, 379-390, 1997 | 229 | 1997 |
Modeling the spread of influence on the blogosphere A Java, P Kolari, T Finin, T Oates UMBC TR-CS-06-03, 2006 | 227 | 2006 |
Cooperative information-gathering: a distributed problem-solving approach T Oates, MVN Prasad, VR Lesser IEE Proceedings-Software 144 (1), 72-88, 1997 | 174 | 1997 |
Identifying distinctive subsequences in multivariate time series by clustering T Oates Proceedings of the fifth ACM SIGKDD international conference on Knowledge …, 1999 | 145 | 1999 |
A method for clustering the experiences of a mobile robot that accords with human judgments T Oates, MD Schmill, PR Cohen AAAI/IAAI, 846-851, 2000 | 137 | 2000 |
Searching for structure in multiple streams of data T Oates, PR Cohen ICML 96, 346-354, 1996 | 133 | 1996 |
A review of recent research in metareasoning and metalearning ML Anderson, T Oates AI Magazine 28 (1), 12-12, 2007 | 118 | 2007 |
Time series anomaly discovery with grammar-based compression. P Senin, J Lin, X Wang, T Oates, S Gandhi, AP Boedihardjo, C Chen, ... Edbt, 481-492, 2015 | 116 | 2015 |
A flexible multichannel EEG feature extractor and classifier for seizure detection A Page, C Sagedy, E Smith, N Attaran, T Oates, T Mohsenin IEEE Transactions on Circuits and Systems II: Express Briefs 62 (2), 109-113, 2014 | 116 | 2014 |
Deep belief networks used on high resolution multichannel electroencephalography data for seizure detection JT Turner, A Page, T Mohsenin, T Oates 2014 aaai spring symposium series, 2014 | 114 | 2014 |
Grammarviz 2.0: a tool for grammar-based pattern discovery in time series P Senin, J Lin, X Wang, T Oates, S Gandhi, AP Boedihardjo, C Chen, ... Machine Learning and Knowledge Discovery in Databases: European Conference …, 2014 | 114 | 2014 |
Hierarchical bayesian models for latent attribute detection in social media D Rao, M Paul, C Fink, D Yarowsky, T Oates, G Coppersmith Proceedings of the international AAAI conference on web and social media 5 …, 2011 | 110 | 2011 |
Using dynamic time warping to bootstrap HMM-based clustering of time series T Oates, L Firoiu, PR Cohen Sequence learning: Paradigms, algorithms, and applications, 35-52, 2001 | 109 | 2001 |
Large Datasets Lead to Overly Complex Models: An Explanation and a Solution. T Oates, DD Jensen KDD, 294-298, 1998 | 108 | 1998 |