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Juha Karhunen
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- affiliation: Aalto University, Department of Computer Science
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2010 – 2019
- 2019
- [j30]Topi Toosi, Miki Sirola, Jarkko Laukkanen, Mark van Heeswijk, Juha Karhunen:
Method for Detecting aging Related Failures of Process Sensors via noise signal Measurement. Int. J. Comput. 18: 135-146 (2019) - 2018
- [j29]Mika Juuti, Francesco Corona
, Juha Karhunen:
Stochastic discriminant analysis for linear supervised dimension reduction. Neurocomputing 291: 136-150 (2018) - 2017
- [j28]Paolo Palumbo, Luiza Sayfullina, Dmitriy Komashinskiy, Emil Eirola
, Juha Karhunen:
A pragmatic android malware detection procedure. Comput. Secur. 70: 689-701 (2017) - [c42]Topi Toosi, Miki Sirola, Jarkko Laukkanen, Mark van Heeswijk, Juha Karhunen:
Detecting aging of process sensors with noise signal measurement. IDAACS 2017: 35-40 - [c41]Satoru Ishikawa, Jorma Laaksonen, Juha Karhunen:
Image pseudo tag generation with Deep Boltzmann machine anc topic-concept similarity map. IJCNN 2017: 1305-1312 - 2016
- [c40]Huiling Wang, Tapani Raiko, Lasse Lensu, Tinghuai Wang, Juha Karhunen:
Semi-supervised Domain Adaptation for Weakly Labeled Semantic Video Object Segmentation. ACCV (1) 2016: 163-179 - [c39]Luiza Sayfullina, Emil Eirola, Dmitry Komashinsky, Paolo Palumbo, Juha Karhunen:
Android Malware Detection: Building Useful Representations. ICMLA 2016: 201-206 - [c38]Alexander Grigorievskiy, Juha Karhunen:
Gaussian Process kernels for popular state-space time series models. IJCNN 2016: 3354-3363 - [c37]Chen Zhao, Mark van Heeswijk, Juha Karhunen:
Air quality forecasting using neural networks. SSCI 2016: 1-7 - [i4]Huiling Wang, Tapani Raiko, Lasse Lensu, Tinghuai Wang, Juha Karhunen:
Semi-Supervised Domain Adaptation for Weakly Labeled Semantic Video Object Segmentation. CoRR abs/1606.02280 (2016) - [i3]Matti Lankinen, Hannes Heikinheimo, Pyry Takala, Tapani Raiko, Juha Karhunen:
A Character-Word Compositional Neural Language Model for Finnish. CoRR abs/1612.03266 (2016) - 2015
- [j27]Anton Akusok, Yoan Miche, Juha Karhunen, Kaj-Mikael Björk, Rui Nian, Amaury Lendasse:
Arbitrary Category Classification of Websites Based on Image Content. IEEE Comput. Intell. Mag. 10(2): 30-41 (2015) - [c36]Mika Juuti, Francesco Corona
, Juha Karhunen:
Stochastic Discriminant Analysis. IJCNN 2015: 1-8 - [c35]Mathias Berglund, Tapani Raiko, Mikko Honkala, Leo Kärkkäinen, Akos Vetek, Juha Karhunen:
Bidirectional Recurrent Neural Networks as Generative Models. NIPS 2015: 856-864 - [c34]Luiza Sayfullina, Emil Eirola
, Dmitry Komashinsky, Paolo Palumbo, Yoan Miché, Amaury Lendasse, Juha Karhunen:
Efficient Detection of Zero-day Android Malware Using Normalized Bernoulli Naive Bayes. TrustCom/BigDataSE/ISPA (1) 2015: 198-205 - [i2]Mathias Berglund, Tapani Raiko, Mikko Honkala, Leo Kärkkäinen, Akos Vetek, Juha Karhunen:
Bidirectional Recurrent Neural Networks as Generative Models - Reconstructing Gaps in Time Series. CoRR abs/1504.01575 (2015) - 2014
- [c33]Emil Eirola
, Amaury Lendasse, Juha Karhunen:
Variable selection for regression problems using Gaussian mixture models to estimate mutual information. IJCNN 2014: 1606-1613 - 2013
- [j26]Juha Karhunen, Tele Hao, Jarkko Ylipaavalniemi
:
Finding dependent and independent components from related data sets: A generalized canonical correlation analysis based method. Neurocomputing 113: 153-167 (2013) - [c32]KyungHyun Cho, Tapani Raiko, Alexander Ilin, Juha Karhunen:
A Two-Stage Pretraining Algorithm for Deep Boltzmann Machines. ICANN 2013: 106-113 - 2012
- [j25]Jaakko Luttinen, Alexander Ilin, Juha Karhunen:
Bayesian Robust PCA of Incomplete Data. Neural Process. Lett. 36(2): 189-202 (2012) - [c31]Juha Karhunen, Tele Hao, Jarkko Ylipaavalniemi
:
A Canonical Correlation Analysis Based Method for Improving BSS of Two Related Data Sets. LVA/ICA 2012: 91-98 - [c30]Tele Hao, Tapani Raiko, Alexander Ilin, Juha Karhunen:
Gated Boltzmann Machine in Texture Modeling. ICANN (2) 2012: 124-131 - [c29]Juha Karhunen, Tele Hao, Jarkko Ylipaavalniemi
:
A generalized canonical correlation analysis based method for blind source separation from related data sets. IJCNN 2012: 1-9 - [i1]Markus Harva, Tapani Raiko, Antti Honkela, Harri Valpola, Juha Karhunen:
Bayes Blocks: An Implementation of the Variational Bayesian Building Blocks Framework. CoRR abs/1207.1380 (2012) - 2011
- [c28]Juha Karhunen, Tele Hao:
Finding dependent and independent components from two related data sets. IJCNN 2011: 457-466 - 2010
- [j24]Antti Honkela, Tapani Raiko, Mikael Kuusela, Matti Tornio, Juha Karhunen:
Approximate Riemannian Conjugate Gradient Learning for Fixed-Form Variational Bayes. J. Mach. Learn. Res. 11: 3235-3268 (2010)
2000 – 2009
- 2009
- [c27]Jaakko Luttinen, Alexander Ilin, Juha Karhunen:
Bayesian Robust PCA for Incomplete Data. ICA 2009: 66-73 - [c26]Mikael Kuusela, Tapani Raiko, Antti Honkela, Juha Karhunen:
A gradient-based algorithm competitive with variational Bayesian EM for mixture of Gaussians. IJCNN 2009: 1688-1695 - 2007
- [j23]Antti Honkela, Harri Valpola, Alexander Ilin, Juha Karhunen:
Blind separation of nonlinear mixtures by variational Bayesian learning. Digit. Signal Process. 17(5): 914-934 (2007) - [j22]Juha Karhunen, Tomas Ukkonen:
Extending ICA for finding jointly dependent components from two related data sets. Neurocomputing 70(16-18): 2969-2979 (2007) - [j21]Tapani Raiko, Harri Valpola, Markus Harva, Juha Karhunen:
Building Blocks for Variational Bayesian Learning of Latent Variable Models. J. Mach. Learn. Res. 8: 155-201 (2007) - [c25]Tapani Raiko, Alexander Ilin, Juha Karhunen:
Principal Component Analysis for Large Scale Problems with Lots of Missing Values. ECML 2007: 691-698 - [c24]Antti Honkela, Matti Tornio, Tapani Raiko, Juha Karhunen:
Natural Conjugate Gradient in Variational Inference. ICONIP (2) 2007: 305-314 - [c23]Tapani Raiko, Alexander Ilin, Juha Karhunen:
Principal Component Analysis for Sparse High-Dimensional Data. ICONIP (1) 2007: 566-575 - 2006
- [j20]Karthikesh Raju, Tapani Ristaniemi, Juha Karhunen, Erkki Oja:
Jammer suppression in DS-CDMA arrays using independent component analysis. IEEE Trans. Wirel. Commun. 5(1): 77-82 (2006) - [c22]Tapani Raiko, Matti Tornio, Antti Honkela, Juha Karhunen:
State Inference in Variational Bayesian Nonlinear State-Space Models. ICA 2006: 222-229 - [c21]Juha Karhunen, Tomas Ukkonen:
Generalizing Independent Component Analysis for Two Related Data Sets. IJCNN 2006: 843-850 - 2005
- [c20]Markus Harva, Tapani Raiko, Antti Honkela, Harri Valpola, Juha Karhunen:
Bayes Blocks: An Implementation of the Variational Bayesian Building Blocks Framework. UAI 2005: 259-266 - 2004
- [j19]Christian Jutten, Juha Karhunen:
Advances in blind source separation (BSS) and independent component analysis (ICA) for nonlinear mixtures. Int. J. Neural Syst. 14(5): 267-292 (2004) - [j18]Harri Valpola, Markus Harva, Juha Karhunen:
Hierarchical models of variance sources. Signal Process. 84(2): 267-282 (2004) - 2003
- [j17]Harri Valpola, Erkki Oja, Alexander Ilin, Antti Honkela, Juha Karhunen:
Nonlinear Blind Source Separation by Variational Bayesian Learning. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 86-A(3): 532-541 (2003) - [j16]Antti Honkela, Harri Valpola, Juha Karhunen:
Accelerating Cyclic Update Algorithms for Parameter Estimation by Pattern Searches. Neural Process. Lett. 17(2): 191-203 (2003) - 2002
- [j15]Harri Valpola, Juha Karhunen:
An Unsupervised Ensemble Learning Method for Nonlinear Dynamic State-Space Models. Neural Comput. 14(11): 2647-2692 (2002) - [c19]Tapani Ristaniemi, Karthikesh Raju, Juha Karhunen:
Jammer mitigation in DS-CDMA array system using independent component analysis. ICC 2002: 232-236 - [c18]Karthikesh Raju, Tapani Ristaniemi, Juha Karhunen, A. Oja:
Suppression of bit-pulsed jammer signals in DS-CDMA array system using independent component analysis. ISCAS (1) 2002: 189-192 - [c17]Tapani Ristaniemi, Karthikesh Raju, Juha Karhunen, Erkki Oja:
Jammer cancellation in DS-CDMA arrays: pre and post switching of ICA and RAKE. NNSP 2002: 495-504 - 2001
- [b1]Aapo Hyvärinen, Juha Karhunen, Erkki Oja:
Independent Component Analysis. Wiley 2001, ISBN 0-471-40540-X, pp. 1-475 - 2000
- [j14]Juha Karhunen, Simona Malaroiu, Mika Ilmoniemi:
Local Linear Independent Component Analysis Based on Clustering. Int. J. Neural Syst. 10(6): 439-451 (2000) - [c16]Razvan Cristescu, Tapani Ristaniemi, Jyrki Joutsensalo, Juha Karhunen:
Blind separation of convolved mixtures for CDMA systems. EUSIPCO 2000: 1-4 - [c15]Razvan Cristescu, Tapani Ristaniemi, Jyrki Joutsensalo, Juha Karhunen:
CDMA delay estimation using fast ICA algorithm. PIMRC 2000: 1117-1120
1990 – 1999
- 1999
- [j13]Xavier Giannakopoulos, Juha Karhunen, Erkki Oja:
An Experimental Comparison of Neural Algorithms for Independent Component Analysis and Blind Separation. Int. J. Neural Syst. 9(2): 99-114 (1999) - [j12]Andrzej Cichocki
, Juha Karhunen, Wlodzimierz Kasprzak, Ricardo Vigário
:
Neural networks for blind separation with unknown number of sources. Neurocomputing 24(1-3): 55-93 (1999) - [c14]Juha Karhunen, Simona Malaroiu:
Locally linear independent component analysis. IJCNN 1999: 882-887 - [c13]Xavier Giannakopoulos, Juha Karhunen, Erkki Oja:
A comparison of neural ICA algorithms using real-world data. IJCNN 1999: 888-893 - 1998
- [j11]Juha Karhunen, Petteri Pajunen, Erkki Oja:
The nonlinear PCA criterion in blind source separation: Relations with other approaches. Neurocomputing 22(1-3): 5-20 (1998) - [j10]Juha Karhunen:
Principal component neural networks - Theory and applications - By K.I. Diamantaras and S.Y. Kung. John Wiley, New York, 1996. xii+255 pp. ISBN 0-471-05436-4. Pattern Anal. Appl. 1(1): 74-75 (1998) - [c12]Visa Koivunen, Petteri Pajunen, Juha Karhunen, Erkki Oja:
Blind separation from ε-contaminated mixtures. EUSIPCO 1998: 1-4 - 1997
- [j9]Juha Karhunen, Andrzej Cichocki
, Wlodzimierz Kasprzak, Petteri Pajunen:
On Neural Blind Separation with Noise Suppression and Redundancy Reduction. Int. J. Neural Syst. 8(2): 219-237 (1997) - [j8]Petteri Pajunen, Juha Karhunen:
Least-Squares Methods for Blind Source Separation Based on Nonlinear PCA. Int. J. Neural Syst. 8(5-6): 601-612 (1997) - [j7]Juha Karhunen, Erkki Oja, Liuyue Wang, Ricardo Vigário
, Jyrki Joutsensalo:
A class of neural networks for independent component analysis. IEEE Trans. Neural Networks 8(3): 486-504 (1997) - [c11]Erkki Oja, Juha Karhunen, Aapo Hyvärinen:
From Neural Principal Components to Neural Independent Components. ICANN 1997: 519-528 - [c10]Petteri Pajunen, Juha Karhunen:
A Maximum Likelihood Approach to Nonlinear Blind Source Separation. ICANN 1997: 541-546 - [c9]Juha Karhunen, Aapo Hyvärinen, Ricardo Vigário, Jarmo Hurri, Erkki Oja:
Applications of neural blind separation to signal and image processing. ICASSP 1997: 131-134 - [c8]Juha Karhunen, Petteri Pajunen:
Blind source separation using least-squares type adaptive algorithms. ICASSP 1997: 3361-3364 - [c7]Juha Karhunen, Petteri Pajunen:
Blind source separation and tracking using nonlinear PCA criterion: a least-squares approach. ICNN 1997: 2147-2152 - 1996
- [j6]Liuyue Wang, Juha Karhunen:
A Unified Neural Bigradient Algorithm for robust PCA and MCA. Int. J. Neural Syst. 7(1): 53-68 (1996) - [c6]Juha Karhunen:
Neural approaches to independent component analysis and source separation. ESANN 1996 - 1995
- [j5]Juha Karhunen, Jyrki Joutsensalo:
Generalizations of principal component analysis, optimization problems, and neural networks. Neural Networks 8(4): 549-562 (1995) - [j4]Jyrki Joutsensalo, Juha Karhunen:
A nonlinear extension of the Generalized Hebbian learning. Neural Process. Lett. 2(1): 5-8 (1995) - [c5]Juha Karhunen, Liuyue Wang, Ricardo Vigário:
Nonlinear PCA type approaches for source separation and independent component analysis. ICNN 1995: 995-1000 - [c4]Liuyue Wang, Juha Karhunen, Erkki Oja:
A bigradient optimization approach for robust PCA, MCA, and source separation. ICNN 1995: 1684-1689 - 1994
- [j3]Juha Karhunen:
Stability of Oja's PCA Subspace Rule. Neural Comput. 6(4): 739-747 (1994) - [j2]Juha Karhunen, Jyrki Joutsensalo:
Representation and separation of signals using nonlinear PCA type learning. Neural Networks 7(1): 113-127 (1994) - 1992
- [j1]Juha Karhunen, Jyrki Joutsensalo:
Sinusoidal frequency estimation by signal subspace approximation. IEEE Trans. Signal Process. 40(12): 2961-2972 (1992) - 1991
- [c3]Juha Karhunen, Jyrki Joutsensalo:
Tracking of sinusoidal frequencies by neural network learning algorithms. ICASSP 1991: 3177-3180 - [c2]Juha Karhunen, Jyrki Joutsensalo:
Robust MUSIC based on direct signal subspace estimation. ICASSP 1991: 3357-3360
1980 – 1989
- 1984
- [c1]Juha Karhunen:
Adaptive algorithms for estimating eigenvectors of correlation type matrices. ICASSP 1984: 592-595
Coauthor Index
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