Time series classification using diversified Ensemble Deep Random Vector Functional Link and Resnet features
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Ponnuthurai N. Suganthan | Rakesh Katuwal | Wen Xin Cheng | P. Suganthan | Wen Xin Cheng | Rakesh Katuwal
[1] Le Zhang,et al. Visual Tracking With Convolutional Random Vector Functional Link Network , 2017, IEEE Transactions on Cybernetics.
[2] Bin Ma,et al. Convolutional neural network with multi-task learning scheme for acoustic scene classification , 2017, 2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC).
[3] Germain Forestier,et al. Deep learning for time series classification: a review , 2018, Data Mining and Knowledge Discovery.
[4] Jason Lines,et al. Classification of time series by shapelet transformation , 2013, Data Mining and Knowledge Discovery.
[5] Ying Wah Teh,et al. Deep learning algorithms for human activity recognition using mobile and wearable sensor networks: State of the art and research challenges , 2018, Expert Syst. Appl..
[6] Y. Takefuji,et al. Functional-link net computing: theory, system architecture, and functionalities , 1992, Computer.
[7] Eamonn J. Keogh,et al. The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances , 2016, Data Mining and Knowledge Discovery.
[8] Robert P. W. Duin,et al. Feedforward neural networks with random weights , 1992, Proceedings., 11th IAPR International Conference on Pattern Recognition. Vol.II. Conference B: Pattern Recognition Methodology and Systems.
[9] Jason Lines,et al. Time-Series Classification with COTE: The Collective of Transformation-Based Ensembles , 2015, IEEE Trans. Knowl. Data Eng..
[10] George C. Runger,et al. A time series forest for classification and feature extraction , 2013, Inf. Sci..
[11] Bolei Zhou,et al. Learning Deep Features for Discriminative Localization , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[12] George C. Runger,et al. A Bag-of-Features Framework to Classify Time Series , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[13] Najdan Vukovic,et al. A comprehensive experimental evaluation of orthogonal polynomial expanded random vector functional link neural networks for regression , 2017, Appl. Soft Comput..
[14] P. N. Suganthan,et al. Random Vector Functional Link Neural Network based Ensemble Deep Learning , 2019, Pattern Recognit..
[15] Swagatam Das,et al. Improving the Performance of Neural Networks with an Ensemble of Activation Functions , 2020, 2020 International Joint Conference on Neural Networks (IJCNN).
[16] Janez Demsar,et al. Statistical Comparisons of Classifiers over Multiple Data Sets , 2006, J. Mach. Learn. Res..
[17] Jun Wang,et al. Multivariate Temporal Convolutional Network: A Deep Neural Networks Approach for Multivariate Time Series Forecasting , 2019, Electronics.
[18] Le Zhang,et al. An ensemble of decision trees with random vector functional link networks for multi-class classification , 2017, Appl. Soft Comput..
[19] Jason Lines,et al. Time series classification with ensembles of elastic distance measures , 2015, Data Mining and Knowledge Discovery.
[20] Ajay M. Patrikar,et al. Multi-Activation Hidden Units for Neural Networks with Random Weights , 2020, ArXiv.
[21] Geoffrey E. Hinton,et al. Rectified Linear Units Improve Restricted Boltzmann Machines , 2010, ICML.
[22] Xindong Wu,et al. 10 Challenging Problems in Data Mining Research , 2006, Int. J. Inf. Technol. Decis. Mak..
[23] Matteo Terzi,et al. Time-Series Classification Methods: Review and Applications to Power Systems Data , 2018 .
[24] Tomasz Górecki,et al. Using derivatives in time series classification , 2012, Data Mining and Knowledge Discovery.
[25] Tomasz Górecki,et al. Non-isometric transforms in time series classification using DTW , 2014, Knowl. Based Syst..
[26] George C. Runger,et al. Time series representation and similarity based on local autopatterns , 2016, Data Mining and Knowledge Discovery.
[27] Yoh-Han Pao,et al. Adaptive pattern recognition and neural networks , 1989 .
[28] Jeffrey Dean,et al. Scalable and accurate deep learning with electronic health records , 2018, npj Digital Medicine.
[29] Javier Del Ser,et al. On-line Elastic Similarity Measures for time series , 2019, Pattern Recognit..
[30] Lifeng Shen,et al. Time series classification with Echo Memory Networks , 2019, Neural Networks.
[31] Anthony J. Bagnall,et al. Binary Shapelet Transform for Multiclass Time Series Classification , 2015, Trans. Large Scale Data Knowl. Centered Syst..
[32] Ling Tang,et al. A non-iterative decomposition-ensemble learning paradigm using RVFL network for crude oil price forecasting , 2017, Appl. Soft Comput..
[33] Houshang Darabi,et al. LSTM Fully Convolutional Networks for Time Series Classification , 2017, IEEE Access.
[34] Lars Schmidt-Thieme,et al. Learning time-series shapelets , 2014, KDD.
[35] Hubert A.B. Te Braake,et al. Random activation weight neural net (RAWN) for fast non-iterative training. , 1995 .
[36] Xiaohui Peng,et al. Deep Learning for Sensor-based Activity Recognition: A Survey , 2017, Pattern Recognit. Lett..
[37] David J. Sheskin,et al. Handbook of Parametric and Nonparametric Statistical Procedures , 1997 .
[38] Csaba Tóth,et al. Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances , 2019, ICML.
[39] Qiang Chen,et al. Network In Network , 2013, ICLR.
[40] P. N. Suganthan,et al. Benchmarking Ensemble Classifiers with Novel Co-Trained Kernal Ridge Regression and Random Vector Functional Link Ensembles [Research Frontier] , 2017, IEEE Computational Intelligence Magazine.
[41] Ponnuthurai N. Suganthan,et al. On the origins of randomization-based feedforward neural networks , 2021, Appl. Soft Comput..
[42] Patrick Schäfer. The BOSS is concerned with time series classification in the presence of noise , 2014, Data Mining and Knowledge Discovery.
[43] Bijaya K. Panigrahi,et al. Indian summer monsoon rainfall prediction: A comparison of iterative and non-iterative approaches , 2017, Appl. Soft Comput..
[44] Christian Lebiere,et al. The Cascade-Correlation Learning Architecture , 1989, NIPS.
[45] Tim Oates,et al. Time series classification from scratch with deep neural networks: A strong baseline , 2016, 2017 International Joint Conference on Neural Networks (IJCNN).
[46] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[47] John Cristian Borges Gamboa,et al. Deep Learning for Time-Series Analysis , 2017, ArXiv.
[48] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.