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* [[Online Tensor Decompositions]]<ref>{{Cite journal |last1=Gujral |first1=Ekta |last2=Pasricha |first2=Ravdeep |last3=Papalexakis |first3=Evangelos E. |editor-first1=Martin |editor-first2=Dino |editor-last1=Ester |editor-last2=Pedreschi |title=SamBaTen: Sampling-based Batch Incremental Tensor Decomposition|journal=Proceedings of the 2018 SIAM International Conference on Data Mining |date=7 May 2018 |doi=10.1137/1.9781611975321|isbn=978-1-61197-532-1 |s2cid=21674935 }}</ref><ref>{{Cite book |last1=Gujral |first1=Ekta |last2=Papalexakis |first2=Evangelos E. |title=2020 IEEE 7th International Conference on Data Science and Advanced Analytics (DSAA) |chapter=OnlineBTD: Streaming Algorithms to Track the Block Term Decomposition of Large Tensors |date=9 October 2020 |pages=168–177 |doi=10.1109/DSAA49011.2020.00029|isbn=978-1-7281-8206-3 |s2cid=227123356 }}</ref><ref name="ektagujral">{{Cite arXiv|last=Gujral |first=Ekta |date=2022 |title=Modeling and Mining Multi-Aspect Graphs With Scalable Streaming Tensor Decomposition |class=cs.SI |eprint=2210.04404}}</ref>
* [[hierarchical Tucker decomposition]];<ref name=Vasilescu2019>{{cite conference |first1=M.A.O.|last1=Vasilescu|first2=E.|last2=Kim|date=2019|title=Compositional Hierarchical Tensor Factorization: Representing Hierarchical Intrinsic and Extrinsic Causal Factors|conference=In The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD’19): Tensor Methods for Emerging Data Science Challenges |eprint=1911.04180 }}</ref>
* [[block term decomposition]]<ref>{{Cite journal |last=De Lathauwer|first=Lieven |title=Decompositions of a Higher-Order Tensor in Block Terms—Part II: Definitions and Uniqueness |url=http://epubs.siam.org/doi/10.1137/070690729 |journal=SIAM Journal on Matrix Analysis and Applications |year=2008 |volume=30 |issue=3 |pages=1033–1066 |language=en |doi=10.1137/070690729}}</ref><ref>{{citation|first1=M.A.O.|last1=Vasilescu|first2=E.|last2=Kim|first3=X.S.|last3=Zeng|title=CausalX: Causal eXplanations and Block Multilinear Factor Analysis |work=Conference Proc. of the 2020 25th International Conference on Pattern Recognition (ICPR 2020)|year=2021 |pages=10736–10743 |doi=10.1109/ICPR48806.2021.9412780 |arxiv=2102.12853 |isbn=978-1-7281-8808-9 |s2cid=232046205 }}</ref><ref name="Vasilescu2019" /><ref>{{cite
==Notation==
This section introduces basic notations and operations that are widely used in the field.
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