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Kim Batselier
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2020 – today
- 2024
- [c22]Frederiek Wesel, Kim Batselier:
Quantized Fourier and Polynomial Features for more Expressive Tensor Network Models. AISTATS 2024: 1261-1269 - [c21]Eva Memmel, Clara Menzen, Jetze Schuurmans, Frederiek Wesel, Kim Batselier:
Position: Tensor Networks are a Valuable Asset for Green AI. ICML 2024 - [i31]Frederiek Wesel, Kim Batselier:
Tensor Network-Constrained Kernel Machines as Gaussian Processes. CoRR abs/2403.19500 (2024) - [i30]Kim Batselier:
Constructing structured tensor priors for Bayesian inverse problems. CoRR abs/2406.17597 (2024) - [i29]Clara Menzen, Manon Kok, Kim Batselier:
Tensor network square root Kalman filter for online Gaussian process regression. CoRR abs/2409.03276 (2024) - [i28]Frederiek Wesel, Kim Batselier:
A Kernelizable Primal-Dual Formulation of the Multilinear Singular Value Decomposition. CoRR abs/2410.10504 (2024) - 2023
- [c20]Frederiek Wesel, Kim Batselier:
Tensor-based Kernel Machines with Structured Inducing Points for Large and High-Dimensional Data. AISTATS 2023: 8308-8320 - [c19]Seline J. S. de Rooij, Kim Batselier, Borbála Hunyadi:
Enabling Large-Scale Probabilistic Seizure Detection with a Tensor-Network Kalman Filter for LS-SVM. ICASSP Workshops 2023: 1-5 - [c18]Jetze Schuurmans, Kim Batselier, Julian F. P. Kooij:
How Informative is the Approximation Error from Tensor Decomposition for Neural Network Compression? ICLR 2023 - [i27]Jetze T. Schuurmans, Kim Batselier, Julian F. P. Kooij:
How Informative is the Approximation Error from Tensor Decomposition for Neural Network Compression? CoRR abs/2305.05318 (2023) - [i26]Frederiek Wesel, Kim Batselier:
Quantized Fourier and Polynomial Features for more Expressive Tensor Network Models. CoRR abs/2309.05436 (2023) - [i25]Clara Menzen, Eva Memmel, Kim Batselier, Manon Kok:
Projecting basis functions with tensor networks for Gaussian process regression. CoRR abs/2310.20630 (2023) - 2022
- [j22]Lingjie Li, Wenjian Yu, Kim Batselier:
Faster tensor train decomposition for sparse data. J. Comput. Appl. Math. 405: 113972 (2022) - [j21]Cong Chen, Kim Batselier, Wenjian Yu, Ngai Wong:
Kernelized support tensor train machines. Pattern Recognit. 122: 108337 (2022) - [j20]Clara Menzen, Manon Kok, Kim Batselier:
Alternating Linear Scheme in a Bayesian Framework for Low-Rank Tensor Approximation. SIAM J. Sci. Comput. 44(3): 1116- (2022) - [i24]Eva Memmel, Clara Menzen, Jetze Schuurmans, Frederiek Wesel, Kim Batselier:
Towards Green AI with tensor networks - Sustainability and innovation enabled by efficient algorithms. CoRR abs/2205.12961 (2022) - 2021
- [c17]Frederiek Wesel, Kim Batselier:
Large-Scale Learning with Fourier Features and Tensor Decompositions. NeurIPS 2021: 17543-17554 - [i23]Frederiek Wesel, Kim Batselier:
Large-Scale Learning with Fourier Features and Tensor Decompositions. CoRR abs/2109.01545 (2021) - [i22]Maximilian Lucassen, Johan A. K. Suykens, Kim Batselier:
Tensor Network Kalman Filtering for Large-Scale LS-SVMs. CoRR abs/2110.13501 (2021) - 2020
- [j19]Ridvan Karagoz, Kim Batselier:
Nonlinear system identification with regularized Tensor Network B-splines. Autom. 122: 109300 (2020) - [j18]Ching-Yun Ko, Kim Batselier, Luca Daniel, Wenjian Yu, Ngai Wong:
Fast and Accurate Tensor Completion With Total Variation Regularized Tensor Trains. IEEE Trans. Image Process. 29: 6918-6931 (2020) - [j17]Ching-Yun Ko, Cong Chen, Zhuolun He, Yuke Zhang, Kim Batselier, Ngai Wong:
Deep Model Compression and Inference Speedup of Sum-Product Networks on Tensor Trains. IEEE Trans. Neural Networks Learn. Syst. 31(7): 2665-2671 (2020) - [i21]Cong Chen, Kim Batselier, Wenjian Yu, Ngai Wong:
Kernelized Support Tensor Train Machines. CoRR abs/2001.00360 (2020) - [i20]Ridvan Karagoz, Kim Batselier:
Nonlinear system identification with regularized Tensor Network B-splines. CoRR abs/2003.07594 (2020) - [i19]Clara Menzen, Manon Kok, Kim Batselier:
Alternating linear scheme in a Bayesian framework for low-rank tensor approximation. CoRR abs/2012.11228 (2020)
2010 – 2019
- 2019
- [c16]Kim Batselier, Ching-Yun Ko, Ngai Wong:
Extended Kalman Filtering with Low-Rank Tensor Networks for MIMO Volterra System Identification. CDC 2019: 7148-7153 - [c15]Daniel Gedon, Pieter Piscaer, Kim Batselier, Carlas S. Smith, Michel Verhaegen:
Tensor Network Kalman Filter for LTI Systems. EUSIPCO 2019: 1-5 - [c14]Cong Chen, Kim Batselier, Ching-Yun Ko, Ngai Wong:
Matrix Product Operator Restricted Boltzmann Machines. IJCNN 2019: 1-8 - [c13]Cong Chen, Kim Batselier, Ching-Yun Ko, Ngai Wong:
A Support Tensor Train Machine. IJCNN 2019: 1-8 - [i18]Lingjie Li, Wenjian Yu, Kim Batselier:
Faster Tensor Train Decomposition for Sparse Data. CoRR abs/1908.02721 (2019) - [i17]Kim Batselier, Andrzej Cichocki, Ngai Wong:
MERACLE: Constructive layer-wise conversion of a Tensor Train into a MERA. CoRR abs/1912.09775 (2019) - 2018
- [j16]Kim Batselier, Ching Yun Ko, Ngai Wong:
Tensor network subspace identification of polynomial state space models. Autom. 95: 187-196 (2018) - [j15]Kim Batselier, Ngai Wong:
Matrix output extension of the tensor network Kalman filter with an application in MIMO Volterra system identification. Autom. 95: 413-418 (2018) - [j14]Philippe Dreesen, Kim Batselier, Bart De Moor:
Multidimensional realisation theory and polynomial system solving. Int. J. Control 91(12): 2692-2704 (2018) - [j13]Kim Batselier, Wenjian Yu, Luca Daniel, Ngai Wong:
Computing Low-Rank Approximations of Large-Scale Matrices with the Tensor Network Randomized SVD. SIAM J. Matrix Anal. Appl. 39(3): 1221-1244 (2018) - [j12]Zhongming Chen, Kim Batselier, Johan A. K. Suykens, Ngai Wong:
Parallelized Tensor Train Learning of Polynomial Classifiers. IEEE Trans. Neural Networks Learn. Syst. 29(10): 4621-4632 (2018) - [i16]Cong Chen, Kim Batselier, Ching Yun Ko, Ngai Wong:
A Support Tensor Train Machine. CoRR abs/1804.06114 (2018) - [i15]Ching Yun Ko, Kim Batselier, Wenjian Yu, Ngai Wong:
Fast and Accurate Tensor Completion with Tensor Trains: A System Identification Approach. CoRR abs/1804.06128 (2018) - [i14]Philippe Dreesen, Kim Batselier, Bart De Moor:
Multidimensional Realization Theory and Polynomial System Solving. CoRR abs/1805.02253 (2018) - [i13]Kim Batselier:
The trouble with tensor ring decompositions. CoRR abs/1811.03813 (2018) - [i12]Ching Yun Ko, Cong Chen, Yuke Zhang, Kim Batselier, Ngai Wong:
Deep Compression of Sum-Product Networks on Tensor Networks. CoRR abs/1811.03963 (2018) - [i11]Cong Chen, Kim Batselier, Ching-Yun Ko, Ngai Wong:
Matrix Product Operator Restricted Boltzmann Machines. CoRR abs/1811.04608 (2018) - 2017
- [j11]Kim Batselier, Zhongming Chen, Ngai Wong:
A Tensor Network Kalman filter with an application in recursive MIMO Volterra system identification. Autom. 84: 17-25 (2017) - [j10]Kim Batselier, Zhongming Chen, Ngai Wong:
Tensor Network alternating linear scheme for MIMO Volterra system identification. Autom. 84: 26-35 (2017) - [j9]Kim Batselier, Ngai Wong:
Inverse multivariate polynomial root-finding: Numerical implementations of the affine and projective Buchberger-Möller algorithm. J. Comput. Appl. Math. 320: 15-29 (2017) - [j8]Kim Batselier, Ngai Wong:
A constructive arbitrary-degree Kronecker product decomposition of tensors. Numer. Linear Algebra Appl. 24(5) (2017) - [j7]Zheng Zhang, Kim Batselier, Haotian Liu, Luca Daniel, Ngai Wong:
Tensor Computation: A New Framework for High-Dimensional Problems in EDA. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 36(4): 521-536 (2017) - [c12]Cong Chen, Kim Batselier, Mihai Telescu, Stéphane Azou, Noël Tanguy, Ngai Wong:
Tensor-network-based predistorter design for multiple-input multiple-output nonlinear systems. ASICON 2017: 1117-1120 - [c11]Zhongming Chen, Kim Batselier, Haotian Liu, Ngai Wong:
An efficient homotopy-based Poincaré-Lindstedt method for the periodic steady-state analysis of nonlinear autonomous oscillators. ASP-DAC 2017: 283-288 - [i10]Kim Batselier, Wenjian Yu, Luca Daniel, Ngai Wong:
Computing low-rank approximations of large-scale matrices with the Tensor Network randomized SVD. CoRR abs/1707.07803 (2017) - [i9]Kim Batselier, Ngai Wong:
Matrix output extension of the tensor network Kalman filter with an application in MIMO Volterra system identification. CoRR abs/1708.05156 (2017) - [i8]Kim Batselier, Ching Yun Ko, Ngai Wong:
Tensor network subspace identification of polynomial state space models. CoRR abs/1709.08773 (2017) - 2016
- [j6]Kim Batselier, Ngai Wong:
Computing the state difference equations for discrete overdetermined linear systems. Autom. 64: 254-261 (2016) - [j5]Kim Batselier, Ngai Wong:
Symmetric tensor decomposition by an iterative eigendecomposition algorithm. J. Comput. Appl. Math. 308: 69-82 (2016) - [c10]Jian Deng, Haotian Liu, Kim Batselier, Yu-Kwong Kwok, Ngai Wong:
STORM: A nonlinear model order reduction method via symmetric tensor decomposition. ASP-DAC 2016: 557-562 - [c9]Kim Batselier, Zhongming Chen, Haotian Liu, Ngai Wong:
A tensor-based volterra series black-box nonlinear system identification and simulation framework. ICCAD 2016: 17 - [i7]Kim Batselier, Zhongming Chen, Ngai Wong:
Tensor Train alternating linear scheme for MIMO Volterra system identification. CoRR abs/1607.00127 (2016) - [i6]Zheng Zhang, Kim Batselier, Haotian Liu, Luca Daniel, Ngai Wong:
Tensor Computation: A New Framework for High-Dimensional Problems in EDA. CoRR abs/1610.04272 (2016) - [i5]Kim Batselier, Zhongming Chen, Ngai Wong:
A Tensor Network Kalman filter with an application in recursive MIMO Volterra system identification. CoRR abs/1610.05434 (2016) - [i4]Zhongming Chen, Kim Batselier, Johan A. K. Suykens, Ngai Wong:
Parallelized Tensor Train Learning of Polynomial Classifiers. CoRR abs/1612.06505 (2016) - 2015
- [j4]Kim Batselier, Haotian Liu, Ngai Wong:
A Constructive Algorithm for Decomposing a Tensor into a Finite Sum of Orthonormal Rank-1 Terms. SIAM J. Matrix Anal. Appl. 36(3): 1315-1337 (2015) - [c8]Kim Batselier, Quan Chen, Ngai Wong:
An adaptive dynamical low-rank tensor approximation scheme for fast circuit simulation. ASICON 2015: 1-4 - [c7]Haotian Liu, Xiaoyan Y. Z. Xiong, Kim Batselier, Lijun Jiang, Luca Daniel, Ngai Wong:
STAVES: Speedy Tensor-Aided Volterra-Based Electronic Simulator. ICCAD 2015: 583-588 - [i3]Kim Batselier, Ngai Wong:
A constructive arbitrary-degree Kronecker product decomposition of tensors. CoRR abs/1507.08805 (2015) - 2014
- [j3]Kim Batselier, Philippe Dreesen, Bart De Moor:
A fast recursive orthogonalization scheme for the Macaulay matrix. J. Comput. Appl. Math. 267: 20-32 (2014) - [j2]Kim Batselier, Philippe Dreesen, Bart De Moor:
The Canonical Decomposition of Cnd and Numerical Gröbner and Border Bases. SIAM J. Matrix Anal. Appl. 35(4): 1242-1264 (2014) - [c6]Jian Deng, Kim Batselier, Yang Zhang, Ngai Wong:
An Efficient Two-level DC Operating Points Finder for Transistor Circuits. DAC 2014: 117:1-117:6 - [c5]Haotian Liu, Kim Batselier, Ngai Wong:
A novel linear algebra method for the determination of periodic steady states of nonlinear oscillators. ICCAD 2014: 611-617 - [i2]Kim Batselier, Haotian Liu, Ngai Wong:
A Constructive Algorithm for Decomposing a Tensor into a Finite Sum of Orthonormal Rank-1 Terms. CoRR abs/1407.1593 (2014) - [i1]Kim Batselier, Ngai Wong:
Symmetric Tensor Decomposition by an Iterative Eigendecomposition Algorithm. CoRR abs/1409.4926 (2014) - 2013
- [j1]Kim Batselier, Philippe Dreesen, Bart De Moor:
The Geometry of Multivariate Polynomial Division and Elimination. SIAM J. Matrix Anal. Appl. 34(1): 102-125 (2013) - 2012
- [c4]Kim Batselier, Philippe Dreesen, Bart De Moor:
maximum likelihood estimation and polynomial system solving. ESANN 2012 - [c3]Philippe Dreesen, Kim Batselier, Bart De Moor:
Weighted/Structured Total Least Squares problems and polynomial system solving. ESANN 2012 - [c2]Dries Geebelen, Kim Batselier, Philippe Dreesen, Marco Signoretto, Johan A. K. Suykens, Bart De Moor, Joos Vandewalle:
Joint Regression and Linear Combination of Time Series for Optimal Prediction. ESANN 2012 - 2010
- [c1]Kim Batselier, Bart De Moor:
Maximum likelihood and polynomial system solving. BIBM Workshops 2010: 819-820
Coauthor Index
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last updated on 2024-11-26 21:40 CET by the dblp team
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