| Intelligent laser welding through representation, prediction, and control learning: An architecture with deep neural networks and reinforcement learning J Günther, PM Pilarski, G Helfrich, H Shen, K Diepold Mechatronics 34, 1-11, 2016 | 191 | 2016 |
| Joint matrices decompositions and blind source separation: A survey of methods, identification, and applications G Chabriel, M Kleinsteuber, E Moreau, H Shen, P Tichavsky, A Yeredor IEEE Signal Processing Magazine 31 (3), 34-43, 2014 | 157 | 2014 |
| First steps towards an intelligent laser welding architecture using deep neural networks and reinforcement learning J Günther, PM Pilarski, G Helfrich, H Shen, K Diepold 2nd International Conference on System-Integrated Intelligence: Challenges …, 2014 | 112 | 2014 |
| Fast kernel-based independent component analysis H Shen, S Jegelka, A Gretton IEEE transactions on signal processing 57 (9), 3498-3511, 2009 | 93 | 2009 |
| Blind source separation with compressively sensed linear mixtures M Kleinsteuber, H Shen IEEE signal processing letters 19 (2), 107-110, 2011 | 46 | 2011 |
| Local convergence analysis of FastICA and related algorithms H Shen, M Kleinsteuber, K Hüper Neural Networks, IEEE Transactions on 19 (6), 1022-1032, 2008 | 44 | 2008 |
| Reconstructible nonlinear dimensionality reduction via joint dictionary learning X Wei, H Shen, Y Li, X Tang, F Wang, M Kleinsteuber, YL Murphey IEEE transactions on neural networks and learning systems 30 (1), 175-189, 2018 | 41 | 2018 |
| Towards a mathematical understanding of the difficulty in learning with feedforward neural networks H Shen Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 41 | 2018 |
| HRTF customization using multiway array analysis M Rothbucher, M Durkovic, H Shen, K Diepold 18th European Signal Processing Conference, EUSIPCO 2010, 229-233, 2010 | 31 | 2010 |
| Formation control using GQ (λ) reinforcement learning M Knopp, C Aykın, J Feldmaier, H Shen 2017 26th IEEE International Symposium on Robot and Human Interactive …, 2017 | 26 | 2017 |
| Video is a cube C Keimel, M Rothbucher, H Shen, K Diepold IEEE Signal Processing Magazine 28 (6), 41-49, 2011 | 23 | 2011 |
| Fast kernel ICA using an approximate newton method H Shen, S Jegelka, A Gretton International Conference on Artificial Intelligence and Statistics, 476-483, 2007 | 23 | 2007 |
| Joint learning sparsifying linear transformation for low-resolution image synthesis and recognition X Wei, Y Li, H Shen, W Xiang, YL Murphey Pattern Recognition 66, 412-424, 2017 | 22 | 2017 |
| Uniqueness analysis of non-unitary matrix joint diagonalization M Kleinsteuber, H Shen IEEE Transactions on Signal Processing 61 (7), 1786-1796, 2013 | 22 | 2013 |
| Complex blind source separation via simultaneous strong uncorrelating transform H Shen, M Kleinsteuber International Conference on Latent Variable Analysis and Signal Separation …, 2010 | 21 | 2010 |
| Trace quotient meets sparsity: A method for learning low dimensional image representations X Wei, H Shen, M Kleinsteuber Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016 | 19 | 2016 |
| A conjugate gradient algorithm for blind sensor calibration in sparse recovery H Shen, M Kleinsteuber, C Bilen, R Gribonval Machine Learning for Signal Processing (MLSP), 2013 IEEE International …, 2013 | 17* | 2013 |
| Dynamical Textures Modeling via Joint Video Dictionary Learning X Wei, Y Li, H Shen, F Chen, M Kleinsteuber, Z Wang IEEE Transactions on Image Processing 26 (6), 2929-2943, 2017 | 16 | 2017 |
| Block Jacobi-type methods for non-orthogonal joint diagonalisation H Shen, K Hüper Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE …, 2009 | 14 | 2009 |
| An adaptive dictionary learning approach for modeling dynamical textures X Wei, H Shen, M Kleinsteuber 2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014 | 13 | 2014 |
Martin KleinsteuberCIO & Lead Data Scientist, Mercateo AG, Munich在 tum.de 的电子邮件经过验证
