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We present DeepMVI, a deep learning method for missing value imputation in multidimensional time-series datasets.
A singular value thresholding algorithm for matrix completion
Jian-Feng Cai, Emmanuel J Candès, and Zuowei Shen. 2010 · 1982
Earlier work this paper cites.
Missing value estimation methods for DNA microarrays
Olga Troyanskaya, Michael Cantor, Gavin Sherlock, Pat Brown, Trevor Hastie, Robert Tibshirani, David Botstein, and Russ B Altman. 2001 · 2001
Earlier work this paper cites.
Single imputation methods
Roderick JA Little and Donald B Rubin. 2002 · 2002
Earlier work this paper cites.
Framewise phoneme classification with bidirectional LSTM and other neural network architectures
Alex Graves and Jürgen Schmidhuber. 2005 · 2005
Earlier work this paper cites.
Dynammo: Mining and summarization of coevolving sequences with missing values. In Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining . 507–516
Lei Li, James McCann, Nancy S Pollard, and Christos Faloutsos. 2009 · 2009
Earlier work this paper cites.
ERACER: A Database Approach for Statistical Inference and Data Cleaning. In Proceedings of the 2010 ACM SIGMOD International Conference on Management of Data
Chris Mayfield, Jennifer Neville, and Sunil Prabhakar. 2010 · 2010
Earlier work this paper cites.
Spectral regularization algorithms for learning large incomplete matrices
Rahul Mazumder, Trevor Hastie, and Robert Tibshirani. 2010 · 2010
Earlier work this paper cites.
Profiler: Integrated statistical analysis and visualization for data quality assessment. In Proceedings of the International Working Conference on Advanced Visual Interfaces . 547–554
Sean Kandel, Ravi Parikh, Andreas Paepcke, Joseph M Hellerstein, and Jeffrey Heer. 2012 · 2012
Earlier work this paper cites.
Temporal regularized matrix factorization for high-dimensional time series prediction. In Advances in neural information processing systems . 847–855
Hsiang-Fu Yu, Nikhil Rao, and Inderjit S Dhillon. 2016 · 2016
Earlier work this paper cites.
Query Optimization for Dynamic Imputation
José Cambronero, John K. Feser, Micah J. Smith, and Samuel Madden. 2017 · 2017
Cited alongside, same era.
DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks
Valentin Flunkert, David Salinas, and Jan Gasthaus. 2017 · 2017
Cited alongside, same era.
Nonnegative matrix factorization for time series recovery from a few temporal aggregates. In International Conference on Machine Learning . PMLR, 2382–2390
Jiali Mei, Yohann De Castro, Yannig Goude, and Georges Hébrail. 2017 · 2017
Cited alongside, same era.
Attention is All you Need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Cited alongside, same era.
Continuous imputation of missing values in streams of pattern-determining time series
Kevin Wellenzohn, Michael H Böhlen, Anton Dignös, Johann Gamper, and Hannes Mitterer. 2017 · 2017
Cited alongside, same era.
Streaming adaptation of deep forecasting models using adaptive recurrent units. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining . 1560–1568
Prathamesh Deshpande and Sunita Sarawagi. 2019 · 2019
Later among the works it cites.
Scalable recovery of missing blocks in time series with high and low cross-correlations
Mourad Khayati, Philippe Cudré-Mauroux, and Michael H Böhlen. 2019 · 2019
Later among the works it cites.
Jasper: An end-to-end convolutional neural acoustic model
Jason Li, Vitaly Lavrukhin, Boris Ginsburg, Ryan Leary, Oleksii Kuchaiev, Jonathan M Cohen, Huyen Nguyen, and Ravi Teja Gadde. 2019b · 2019
Later among the works it cites.
NAOMI: Non-autoregressive multiresolution sequence imputation. In Advances in Neural Information Processing Systems . 11238–11248
Yukai Liu, Rose Yu, Stephan Zheng, Eric Zhan, and Yisong Yue. 2019 · 2019
Later among the works it cites.
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Brits: Bidirectional recurrent imputation for time series
Wei Cao, Dong Wang, Jian Li, Hao Zhou, Lei Li, and Yitan Li. 2018 · 2018
Cited alongside, same era.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
Cited alongside, same era.
Estimating missing data in temporal data streams using multi-directional recurrent neural networks
Jinsung Yoon, William R Zame, and Mihaela van der Schaar. 2018 · 2018
Cited alongside, same era.
Optuna: A Next-generation Hyperparameter Optimization Framework. In Proceedings of the 25rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Takuya Akiba, Shotaro Sano, Toshihiko Yanase, Takeru Ohta, and Masanori Koyama. 2019 · 2019
Cited alongside, same era.
Enhancing the locality and breaking the memory bottleneck of transformer on time series forecasting. In Advances in Neural Information Processing Systems . 5243–5253
Shiyang Li, Xiaoyong Jin, Yao Xuan, Xiyou Zhou, Wenhu Chen, Yu-Xiang Wang, and Xifeng Yan. 2019a
Cited in the paper.
High-dimensional multivariate forecasting with low-rank Gaussian Copula Processes. In Advances in Neural Information Processing Systems . 6827–6837
David Salinas, Michael Bohlke-Schneider, Laurent Callot, Roberto Medico, and Jan Gasthaus. 2019 · 2019
Later among the works it cites.
Rajat Sen, Hsiang-Fu Yu, and Inderjit Dhillon. 2019 · 2019
Later among the works it cites.
Gp-vae: Deep probabilistic time series imputation. In International Conference on Artificial Intelligence and Statistics . PMLR, 1651–1661
Vincent Fortuin, Dmitry Baranchuk, Gunnar Rätsch, and Stephan Mandt. 2020 · 2020
Later among the works it cites.
Mind the gap: an experimental evaluation of imputation of missing values techniques in time series
Mourad Khayati, Alberto Lerner, Zakhar Tymchenko, and Philippe Cudré-Mauroux. 2020 · 2020
Later among the works it cites.
Automating exploratory data analysis via machine learning: An overview. In Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data . 2617–2622
Tova Milo and Amit Somech. 2020 · 2020
Later among the works it cites.