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Time series data has been demonstrated to be crucial in various research fields.
Automatic Early Detection of Amyotrophic Lateral Sclerosis from Intelligible Speech Using Convolutional Neural Networks.. In Interspeech . 1913–1917
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Long short-term memory
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PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals
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Rectified linear units improve restricted boltzmann machines. In Proceedings of the 27th international conference on machine learning (ICML-10) . 807–814
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A kernel two-sample test
Arthur Gretton, Karsten M Borgwardt, Malte J Rasch, Bernhard Schölkopf, and Alexander Smola. 2012 · 2012
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A public domain dataset for human activity recognition using smartphones.. In Esann , Vol. 3. 3
Davide Anguita, Alessandro Ghio, Luca Oneto, Xavier Parra, Jorge Luis Reyes-Ortiz, et al · 2013
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Flying insect classification with inexpensive sensors
Yanping Chen, Adena Why, Gustavo Batista, Agenor Mafra-Neto, and Eamonn Keogh. 2014 · 2014
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Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling
Junyoung Chung, Caglar Gulcehre, KyungHyun Cho, and Yoshua Bengio. 2014 · 2014
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TRISTAN: Real-time analytics on massive time series using sparse dictionary compression. In 2014 IEEE International Conference on Big Data (Big Data) . IEEE, 291–300
Alice Marascu, Pascal Pompey, Eric Bouillet, Michael Wurst, Olivier Verscheure, Martin Grund, and Philippe Cudre-Mauroux. 2014 · 2014
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Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe and Christian Szegedy. 2015 · 2015
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Multi-scale convolutional neural networks for time series classification
Zhicheng Cui, Wenlin Chen, and Yixin Chen. 2016 · 2016
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Deep residual learning for image recognition. In Proceedings of the IEEE conference on computer vision and pattern recognition . 770–778
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016 · 2016
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Condition monitoring of bearing damage in electromechanical drive systems by using motor current signals of electric motors: A benchmark data set for data-driven classification. In PHM Society European Conference , Vol. 3
Christian Lessmeier, James Kuria Kimotho, Detmar Zimmer, and Walter Sextro. 2016 · 2016
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Minimax estimation of maximum mean discrepancy with radial kernels
Ilya O Tolstikhin, Bharath K Sriperumbudur, and Bernhard Schölkopf. 2016 · 2016
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Neural architecture search: A survey
Thomas Elsken, Jan Hendrik Metzen, and Frank Hutter. 2019b · 2017
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Diffusion convolutional recurrent neural network: Data-driven traffic forecasting
Yaguang Li, Rose Yu, Cyrus Shahabi, and Yan Liu. 2017 · 2017
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Instance Normalization: The Missing Ingredient for Fast Stylization
Dmitry Ulyanov, Andrea Vedaldi, and Victor Lempitsky. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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An empirical evaluation of generic convolutional and recurrent networks for sequence modeling
Shaojie Bai, J Zico Kolter, and Vladlen Koltun. 2018 · 2018
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The UCR Time Series Classification Archive
Hoang Anh Dau, Eamonn Keogh, Kaveh Kamgar, Chin-Chia Michael Yeh, Yan Zhu, Shaghayegh Gharghabi, Chotirat Ann Ratanamahatana, Yanping Chen, Bing Hu, Nurjahan Begum, Anthony Bagnall, Abdullah Mueen, Gustavo Batista, and Hexagon-ML. 2018 · 2018
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Development of a lossless data compression algorithm for multichannel environmental monitoring systems. In 2018 XIV International Scientific-Technical Conference on Actual Problems of Electronics Instrument Engineering (APEIE) . IEEE, 483–486
Hussein Sh Mogahed and Alexey G Yakunin. 2018 · 2018
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The UCR time series archive
Hoang Anh Dau, Anthony Bagnall, Kaveh Kamgar, Chin-Chia Michael Yeh, Yan Zhu, Shaghayegh Gharghabi, Chotirat Ann Ratanamahatana, and Eamonn Keogh. 2019 · 2019
Cited alongside, same era.
Neural Architecture Search: A Survey
Thomas Elsken, Jan Hendrik Metzen, and Frank Hutter. 2019a · 2019
Cited alongside, same era.
Multitask learning and benchmarking with clinical time series data
Hrayr Harutyunyan, Hrant Khachatrian, David C. Kale, Greg Ver Steeg, and Aram Galstyan. 2019 · 2019
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Dataset meta-learning from kernel ridge-regression
Timothy Nguyen, Zhourong Chen, and Jaehoon Lee. 2020 · 2020
Cited alongside, same era.
Neural architecture search for time series classification. In 2020 International Joint Conference on Neural Networks (IJCNN) . IEEE, 1–8
Hojjat Rakhshani, Hassan Ismail Fawaz, Lhassane Idoumghar, Germain Forestier, Julien Lepagnot, Jonathan Weber, Mathieu Brévilliers, and Pierre-Alain Muller. 2020 · 2020
Cited alongside, same era.
Dataset distillation using parameter pruning
Guang Li, Ren Togo, Takahiro Ogawa, and Miki Haseyama. 2022 · 2022
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Graph condensation via receptive field distribution matching
Mengyang Liu, Shanchuan Li, Xinshi Chen, and Le Song. 2022a · 2022
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Dataset distillation via factorization
Songhua Liu, Kai Wang, Xingyi Yang, Jingwen Ye, and Xinchao Wang. 2022b · 2022
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Infinite Recommendation Networks: A Data-Centric Approach
Noveen Sachdeva, Mehak Preet Dhaliwal, Carole-Jean Wu, and Julian McAuley. 2022 · 2022
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Cafe: Learning to condense dataset by aligning features. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 12196–12205
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Tongzhou Wang, Jun-Yan Zhu, Antonio Torralba, and Alexei A. Efros. 2020 · 2020
Cited alongside, same era.
Time series data augmentation for deep learning: A survey
Qingsong Wen, Liang Sun, Fan Yang, Xiaomin Song, Jingkun Gao, Xue Wang, and Huan Xu. 2020 · 2020
Cited alongside, same era.
Dataset condensation with gradient matching
Bo Zhao, Konda Reddy Mopuri, and Hakan Bilen. 2020 · 2020
Cited alongside, same era.
Continual learning for multivariate time series tasks with variable input dimensions. In 2021 IEEE International Conference on Data Mining (ICDM) . IEEE, 161–170
Vibhor Gupta, Jyoti Narwariya, Pankaj Malhotra, Lovekesh Vig, and Gautam Shroff. 2021 · 2021
Cited alongside, same era.
Graph condensation for graph neural networks
Wei Jin, Lingxiao Zhao, Shichang Zhang, Yozen Liu, Jiliang Tang, and Neil Shah. 2021 · 2021
Cited alongside, same era.
Dataset distillation with infinitely wide convolutional networks
Timothy Nguyen, Roman Novak, Lechao Xiao, and Jaehoon Lee. 2021 · 2021
Cited alongside, same era.
Dataset condensation with differentiable siamese augmentation. In International Conference on Machine Learning . PMLR, 12674–12685
Bo Zhao and Hakan Bilen. 2021 · 2021
Cited alongside, same era.
Kai Wang, Bo Zhao, Xiangyu Peng, Zheng Zhu, Shuo Yang, Shuo Wang, Guan Huang, Hakan Bilen, Xinchao Wang, and Yang You. 2022 · 2022
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Gerald Woo, Chenghao Liu, Doyen Sahoo, Akshat Kumar, and Steven Hoi. 2022 · 2022
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Unsupervised time-series representation learning with iterative bilinear temporal-spectral fusion. In International Conference on Machine Learning . PMLR, 25038–25054
Ling Yang and Shenda Hong. 2022 · 2022
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Cross reconstruction transformer for self-supervised time series representation learning
Wenrui Zhang, Ling Yang, Shijia Geng, and Shenda Hong. 2022a · 2022
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Self-supervised contrastive pre-training for time series via time-frequency consistency
Xiang Zhang, Ziyuan Zhao, Theodoros Tsiligkaridis, and Marinka Zitnik. 2022b · 2022
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Dataset distillation using neural feature regression
Yongchao Zhou, Ehsan Nezhadarya, and Jimmy Ba. 2022b · 2022
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Time series compression survey
Giacomo Chiarot and Claudio Silvestri. 2023 · 2023
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Minimizing the accumulated trajectory error to improve dataset distillation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 3749–3758
Jiawei Du, Yidi Jiang, Vincent YF Tan, Joey Tianyi Zhou, and Haizhou Li. 2023 · 2023
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Chumeng Liang, Zherui Huang, Yicheng Liu, Zhanyu Liu, Guanjie Zheng, Hanyuan Shi, Kan Wu, Yuhao Du, Fuliang Li, and Zhenhui Li. 2023 · 2023
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FDTI: Fine-grained Deep Traffic Inference with Roadnet-enriched Graph
Zhanyu Liu, Chumeng Liang, Guanjie Zheng, and Hua Wei. 2023a · 2023
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Cross-city Few-Shot Traffic Forecasting via Traffic Pattern Bank
Zhanyu Liu, Guanjie Zheng, and Yanwei Yu. 2023b · 2023
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Dataset Distillation with Convexified Implicit Gradients
Noel Loo, Ramin Hasani, Mathias Lechner, and Daniela Rus. 2023 · 2023
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Datadam: Efficient dataset distillation with attention matching. In Proceedings of the IEEE/CVF International Conference on Computer Vision . 17097–17107
Ahmad Sajedi, Samir Khaki, Ehsan Amjadian, Lucy Z Liu, Yuri A Lawryshyn, and Konstantinos N Plataniotis. 2023 · 2023
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Accelerating dataset distillation via model augmentation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 11950–11959
Lei Zhang, Jie Zhang, Bowen Lei, Subhabrata Mukherjee, Xiang Pan, Bo Zhao, Caiwen Ding, Yao Li, and Dongkuan Xu. 2023 · 2023
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Dataset condensation with distribution matching. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision . 6514–6523
Bo Zhao and Hakan Bilen. 2023 · 2023
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Multi-scale Traffic Pattern Bank for Cross-city Few-shot Traffic Forecasting
Zhanyu Liu, Guanjie Zheng, and Yanwei Yu. 2024b · 2024
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