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Learning to classify time series with limited data is a practical yet challenging problem.
On a space of completely additive functions
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Use of fourier transform infrared spectroscopy and partial least squares regression for the detection of adulteration of strawberry purees
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Pattern extraction for time series classification
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Three myths about dynamic time warping data mining
Ratanamahatana, C. A. and Keogh, E · 2005
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Auditory attention—focusing the searchlight on sound
Fritz, J. B., Elhilali, M., David, S. V., and Shamma, S. A · 2007
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Heartbeat time series classification with support vector machines
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Time series classification using support vector machine with gaussian elastic metric kernel
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A shapelet transform for time series classification
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Predictive modelling of bone ageing
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Classification of time series by shapelet transformation
Hills, J., Lines, J., Baranauskas, E., Mapp, J., and Bagnall, A · 2014
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A review of unsupervised feature learning and deep learning for time-series modeling
Langkvist, M., Karlsson, L., and Loutfi, A · 2014
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A regression approach to speech enhancement based on deep neural networks
Xu, Y., Du, J., Dai, L.-R., and Lee, C.-H · 2014
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Time-series classification with cote: the collective of transformation-based ensembles
Bagnall, A., Lines, J., Hills, J., and Bostrom, A · 2015
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The boss is concerned with time series classification in the presence of noise
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Tensorflow: A system for large-scale machine learning
Abadi, M., Barham, P., Chen, J., Chen, Z., Davis, A., Dean, J., Devin, M., Ghemawat, S., Irving, G., Isard, M., et al · 2016
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Deep residual learning for image recognition
He, K., Zhang, X., Ren, S., and Sun, J · 2016
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Temporal convolutional networks: A unified approach to action segmentation
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Zhou, B., Khosla, A., Lapedriza, A., Oliva, A., and Torralba, A · 2016
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On the properties of the softmax function with application in game theory and reinforcement learning
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The ucr time series archive
Dau, H. A., Bagnall, A., Kamgar, K., Yeh, C.-C. M., Zhu, Y., Gharghabi, S., Ratanamahatana, C. A., and Keogh, E · 2019
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Adversarial reprogramming of neural networks
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Deep learning for time series classification: a review
Fawaz, H. I., Forestier, G., Weber, J., Idoumghar, L., and Muller, P.-A · 2019
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Mina: Multilevel knowledge-guided attention for modeling electrocardiography signals
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Convtimenet: A pre-trained deep convolutional neural network for time series classification
Kashiparekh, K., Narwariya, J., Malhotra, P., Vig, L., and Shroff, G · 2019
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Audio set: An ontology and human-labeled dataset for audio events
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Cnn architectures for large-scale audio classification
Hershey, S., Chaudhuri, S., Ellis, D. P., Gemmeke, J. F., Jansen, A., Moore, R. C., Plakal, M., Platt, D., Saurous, R. A., Seybold, B., et al · 2017
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Modelling auditory attention
Kaya, E. M. and Elhilali, M · 2017
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English conversational telephone speech recognition by humans and machines
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How is visual salience computed in the brain? insights from behaviour, neurobiology and modelling
Veale, R., Hafed, Z. M., and Yoshida, M · 2017
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Time series classification from scratch with deep neural networks: A strong baseline
Wang, Z., Yan, W., and Oates, T · 2017
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A neural attention model for speech command recognition
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Neekhara, P., Hussain, S., Dubnov, S., and Koushanfar, F · 2019
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Enhancing sound texture in cnn-based acoustic scene classification
Wu, Y. and Lee, T · 2019
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Fast and accurate time series classification through supervised interval search
Cabello, N., Naghizade, E., Qi, J., and Kulik, L · 2020
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Warp: Word-level adversarial reprogramming
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Heittola, T., Mesaros, A., and Virtanen, T · 2020
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Device-robust acoustic scene classification based on two-stage categorization and data augmentation
Hu, H., Yang, C.-H. H., Xia, X., Bai, X., Tang, X., Wang, Y., Niu, S., Chai, L., Li, J., Zhu, H., et al · 2020
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Reprogramming of neural networks: A new and improved machine learning technique
Kloberdanz, E · 2020
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A primer on zeroth-order optimization in signal processing and machine learning
Liu, S., Chen, P.-Y., Kailkhura, B., Zhang, G., Hero, A., and Varshney, P. K · 2020
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Transfer learning without knowing: Reprogramming black-box machine learning models with scarce data and limited resources
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Reprogramming language models for molecular representation learning
Vinod, R., Chen, P.-Y., and Das, P · 2020
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Characterizing speech adversarial examples using self-attention u-net enhancement
Yang, C.-H., Qi, J., Chen, P.-Y., Ma, X., and Lee, C.-H · 2020
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A two-stage approach to device-robust acoustic scene classification
Hu, H., Yang, C.-H. H., Xia, X., Bai, X., Tang, X., Wang, Y., Niu, S., Chai, L., Li, J., Zhu, H., et al · 2021
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Decentralizing feature extraction with quantum convolutional neural network for automatic speech recognition
Yang, C.-H. H., Qi, J., Chen, S. Y.-C., Chen, P.-Y., Siniscalchi, S. M., Ma, X., and Lee, C.-H · 2021
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ESC: Dataset for Environmental Sound Classification
Piczak, K. J · 2025
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