Noise Adaptive Tensor Train Decomposition for Low-Rank Embedding of Noisy Data

[1]  Volker Tresp,et al.  Tensor-Train Recurrent Neural Networks for Video Classification , 2017, ICML.

[2]  Satoshi Nakamura,et al.  Compressing recurrent neural network with tensor train , 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

[3]  K. Selçuk Candan,et al.  nTD: Noise-Profile Adaptive Tensor Decomposition , 2017, WWW.

[4]  Michael Stonebraker,et al.  Detecting Data Errors: Where are we and what needs to be done? , 2016, Proc. VLDB Endow..

[5]  Lee Sael,et al.  SCouT: Scalable coupled matrix-tensor factorization - algorithm and discoveries , 2016, 2016 IEEE 32nd International Conference on Data Engineering (ICDE).

[6]  Reza Zafarani,et al.  Users joining multiple sites: Friendship and popularity variations across sites , 2016, Inf. Fusion.

[7]  F. Maxwell Harper,et al.  The MovieLens Datasets: History and Context , 2016, TIIS.

[8]  K. Selçuk Candan,et al.  Efficient Static and Dynamic In-Database Tensor Decompositions on Chunk-Based Array Stores , 2014, CIKM.

[9]  K. Selçuk Candan,et al.  Focusing Decomposition Accuracy by Personalizing Tensor Decomposition (PTD) , 2014, CIKM.

[10]  K. Selçuk Candan,et al.  LWI-SVD: low-rank, windowed, incremental singular value decompositions on time-evolving data sets , 2014, KDD.

[11]  Paolo Papotti,et al.  RuleMiner: Data quality rules discovery , 2014, 2014 IEEE 30th International Conference on Data Engineering.

[12]  J. Ballani,et al.  Black box approximation of tensors in hierarchical Tucker format , 2013 .

[13]  Lars Grasedyck,et al.  F ¨ Ur Mathematik in Den Naturwissenschaften Leipzig a Projection Method to Solve Linear Systems in Tensor Format a Projection Method to Solve Linear Systems in Tensor Format , 2022 .

[14]  Christos Faloutsos,et al.  GigaTensor: scaling tensor analysis up by 100 times - algorithms and discoveries , 2012, KDD.

[15]  Hisashi Kashima,et al.  Fast Similarity Computation in Factorized Tensors , 2012, SISAP.

[16]  Reinhold Schneider,et al.  The Alternating Linear Scheme for Tensor Optimization in the Tensor Train Format , 2012, SIAM J. Sci. Comput..

[17]  Ivan Oseledets,et al.  Tensor-Train Decomposition , 2011, SIAM J. Sci. Comput..

[18]  Eric C. Chi,et al.  Making Tensor Factorizations Robust to Non-Gaussian Noise , 2010, 1010.3043.

[19]  Subbarao Kambhampati,et al.  SourceRank: relevance and trust assessment for deep web sources based on inter-source agreement , 2010, WWW '10.

[20]  Wei Chu,et al.  Probabilistic Models for Incomplete Multi-dimensional Arrays , 2009, AISTATS.

[21]  P. Cochat,et al.  Et al , 2008, Archives de pediatrie : organe officiel de la Societe francaise de pediatrie.

[22]  Hyunsoo Kim,et al.  Nonnegative Matrix Factorization Based on Alternating Nonnegativity Constrained Least Squares and Active Set Method , 2008, SIAM J. Matrix Anal. Appl..

[23]  Ruslan Salakhutdinov,et al.  Probabilistic Matrix Factorization , 2007, NIPS.

[24]  Rasmus Bro,et al.  Multiway analysis of epilepsy tensors , 2007, ISMB/ECCB.

[25]  Soumen Chakrabarti,et al.  Dynamic personalized pagerank in entity-relation graphs , 2007, WWW '07.

[26]  Philip S. Yu,et al.  Window-based Tensor Analysis on High-dimensional and Multi-aspect Streams , 2006, Sixth International Conference on Data Mining (ICDM'06).

[27]  Brett W. Bader,et al.  Temporal Analysis of Social Networks using Three-way DEDICOM , 2006 .

[28]  Rasmus Bro,et al.  The N-way Toolbox for MATLAB , 2000 .

[29]  Michael I. Jordan,et al.  An Introduction to Variational Methods for Graphical Models , 1999, Machine Learning.

[30]  Sergey Brin,et al.  The Anatomy of a Large-Scale Hypertextual Web Search Engine , 1998, Comput. Networks.

[31]  Geoffrey E. Hinton,et al.  Keeping the neural networks simple by minimizing the description length of the weights , 1993, COLT '93.

[32]  J. Leeuw,et al.  Principal component analysis of three-mode data by means of alternating least squares algorithms , 1980 .

[33]  L. Tucker,et al.  Some mathematical notes on three-mode factor analysis , 1966, Psychometrika.

[34]  K. Candan,et al.  nTD: Noise Adaptive Tensor Decomposition , 2018 .

[35]  Andrzej Cichocki,et al.  Low-Rank Tensor Networks for Dimensionality Reduction and Large-Scale Optimization Problems: Perspectives and Challenges PART 1 , 2016, ArXiv.

[36]  Wolfgang Hackbusch,et al.  An Introduction to Hierarchical (H-) Rank and TT-Rank of Tensors with Examples , 2011, Comput. Methods Appl. Math..

[37]  Radford M. Neal Probabilistic Inference Using Markov Chain Monte Carlo Methods , 2011 .

[38]  Xi Chen,et al.  Temporal Collaborative Filtering with Bayesian Probabilistic Tensor Factorization , 2010, SDM.

[39]  Richard A. Harshman,et al.  Foundations of the PARAFAC procedure: Models and conditions for an "explanatory" multi-model factor analysis , 1970 .