Tim Oates
Cited by
Cited by
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
Efficient progressive sampling
F Provost, D Jensen, T Oates
Proceedings of the fifth ACM SIGKDD international conference on Knowledge …, 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
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
Imaging time-series to improve classification and imputation
Z Wang, T Oates
Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015
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
Modeling the spread of influence on the blogosphere
A Java, P Kolari, T Finin, T Oates
UMBC TR-CS-06-03, 2006
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
Cooperative information-gathering: a distributed problem-solving approach
T Oates, MVN Prasad, VR Lesser
IEE Proceedings-Software 144 (1), 72-88, 1997
Identifying distinctive subsequences in multivariate time series by clustering
T Oates
Proceedings of the fifth ACM SIGKDD international conference on Knowledge …, 1999
Searching for structure in multiple streams of data
T Oates, PR Cohen
ICML 96, 346-354, 1996
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
Large Datasets Lead to Overly Complex Models: An Explanation and a Solution.
T Oates, DD Jensen
KDD, 294-298, 1998
PERUSE: An unsupervised algorithm for finding recurring patterns in time series
T Oates
2002 IEEE International Conference on Data Mining, 2002. Proceedings., 330-337, 2002
Hierarchical bayesian models for latent attribute detection in social media
D Rao, M Paul, C Fink, D Yarowsky, T Oates, G Coppersmith
Fifth International AAAI Conference on Weblogs and Social Media, 2011
A review of recent research in metareasoning and metalearning
ML Anderson, T Oates
AI Magazine 28 (1), 12-12, 2007
Using dynamic time warping to bootstrap HMM-based clustering of time series
T Oates, L Firoiu, PR Cohen
Sequence Learning, 35-52, 2000
Neo: Learning conceptual knowledge by sensorimotor interaction with an environment
PR Cohen, MS Atkin, T Oates, CR Beal
Proceedings of the first international conference on Autonomous agents, 170-177, 1997
Visualizing variable-length time series motifs
Y Li, J Lin, T Oates
Proceedings of the 2012 SIAM international conference on data mining, 895-906, 2012
The metacognitive loop I: Enhancing reinforcement learning with metacognitive monitoring and control for improved perturbation tolerance
ML Anderson, T Oates, W Chong, D Perlis
Journal of Experimental and Theoretical Artificial Intelligence 18 (3), 387-411, 2006
The system can't perform the operation now. Try again later.
Articles 1–20