NMTucker: Non-linear Matryoshka Tucker Decomposition for Financial Time Series Imputation

Author:

Varolgunes Uras1ORCID,Zhou Dan1ORCID,Yu Dantong1ORCID,Uddin Ajim1ORCID

Affiliation:

1. New Jersey Institute of Technology, United States

Publisher

ACM

Reference34 articles.

1. Scalable tensor factorizations for incomplete data

2. Ivana Balažević , Carl Allen , and Timothy  M. Hospedales . 2019. TuckER: Tensor Factorization for Knowledge Graph Completion. arXiv e-prints , Article arXiv:1901.09590 (Jan 2019 ), arXiv:1901.09590 pages. arxiv:1901.09590 [cs.LG] Ivana Balažević, Carl Allen, and Timothy M. Hospedales. 2019. TuckER: Tensor Factorization for Knowledge Graph Completion. arXiv e-prints, Article arXiv:1901.09590 (Jan 2019), arXiv:1901.09590 pages. arxiv:1901.09590 [cs.LG]

3. Turan  G Bali , Amit Goyal , Dashan Huang , Fuwei Jiang , and Quan Wen . 2021. Different strokes: Return predictability across stocks and bonds with machine learning and big data . Swiss Finance Institute , Research Paper Series20-110 ( 2021 ). Turan G Bali, Amit Goyal, Dashan Huang, Fuwei Jiang, and Quan Wen. 2021. Different strokes: Return predictability across stocks and bonds with machine learning and big data. Swiss Finance Institute, Research Paper Series20-110 (2021).

4. Ryan  T Ball and Eric Ghysels . 2018. Automated Earnings Forecasts: Beat Analysts or Combine and Conquer?Management Science 64, 10 ( 2018 ), 4936–4952. Ryan T Ball and Eric Ghysels. 2018. Automated Earnings Forecasts: Beat Analysts or Combine and Conquer?Management Science 64, 10 (2018), 4936–4952.

5. Factor-based imputation of missing values and covariances in panel data of large dimensions

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