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ORCIDJan Larsen
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2010 – 2019
- 2019
[c56]Damian Konrad Kowalczyk, Jan Larsen:
Scalable Privacy-Compliant Virality Prediction on Twitter. AffCon@AAAI 2019: 12-27- [c55]Mikkel N. Schmidt
, Tommy S. Alstrøm, Marcus Svendstorp, Jan Larsen:
Peak Detection and Baseline Correction Using a Convolutional Neural Network. ICASSP 2019: 2757-2761 - 2018
- [j25]Benjamin Johansen, Michael Kai Petersen, Maciej Jan Korzepa, Jan Larsen, Niels Henrik Pontoppidan, Jakob Eg Larsen:
Personalizing the Fitting of Hearing Aids by Learning Contextual Preferences From Internet of Things Data. Comput. 7(1): 1 (2018) - [c54]Maciej Jan Korzepa, Benjamin Johansen, Michael Kai Petersen, Jan Larsen, Jakob Eg Larsen, Niels Henrik Pontoppidan:
Learning Preferences and Soundscapes for Augmented Hearing. IUI Workshops 2018 - [c53]Maciej Jan Korzepa, Benjamin Johansen, Michael Kai Petersen, Jan Larsen, Jakob Eg Larsen, Niels Henrik Pontoppidan:
Modeling User Intents as Context in Smartphone-connected Hearing Aids. UMAP (Adjunct Publication) 2018: 151-155 - [i3]Damian Konrad Kowalczyk, Jan Larsen:
Scalable Privacy-Compliant Virality Prediction on Twitter. CoRR abs/1812.06034 (2018) - 2017
- [c52]Tommy S. Alstrøm, Mikkel N. Schmidt, Tomas Rindzevicius, Anja Boisen, Jan Larsen:
A pseudo-Voigt component model for high-resolution recovery of constituent spectra in Raman spectroscopy. ICASSP 2017: 2317-2321 - [e3]Naonori Ueda, Shinji Watanabe, Tomoko Matsui, Jen-Tzung Chien, Jan Larsen:
27th IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2017, Tokyo, Japan, September 25-28, 2017. IEEE 2017, ISBN 978-1-5090-6341-3 [contents] - 2016
- [e2]Francesco A. N. Palmieri, Aurelio Uncini, Kostas I. Diamantaras, Jan Larsen:
26th IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016, Vietri sul Mare, Salerno, Italy, September 13-16, 2016. IEEE 2016, ISBN 978-1-5090-0746-2 [contents] - [i2]Stina Lyck Carstensen, Jens Madsen, Jan Larsen:
Predicting Changes in Affective States using Neural Networks. CoRR abs/1612.00582 (2016) - 2015
- [j24]Jens Brehm Bagger Nielsen, Jakob Nielsen, Jan Larsen:
Perception-Based Personalization of Hearing Aids Using Gaussian Processes and Active Learning. IEEE ACM Trans. Audio Speech Lang. Process. 23(1): 162-173 (2015) - [j23]Corey Kereliuk, Bob L. Sturm, Jan Larsen:
Deep Learning and Music Adversaries. IEEE Trans. Multim. 17(11): 2059-2071 (2015) - [j22]Saeid Sanei, Paris Smaragdis, Anthony T. S. Ho, Asoke K. Nandi, Jan Larsen:
Guest Editorial: Machine Learning for Signal Processing. J. Signal Process. Syst. 79(2): 113-116 (2015) - [c51]Bob L. Sturm, Corey Kereliuk, Jan Larsen:
¿El Caballo Viejo? Latin Genre Recognition with Deep Learning and Spectral Periodicity. MCM 2015: 335-346 - [c50]Jens Madsen, Bjørn Sand Jensen, Jan Larsen:
Learning Combinations of Multiple Feature Representations for Music Emotion Prediction. ASM@ACM Multimedia 2015: 3-8 - [c49]Corey Kereliuk, Bob L. Sturm, Jan Larsen:
Deep learning, audio adversaries, and music content analysis. WASPAA 2015: 1-5 - [e1]Deniz Erdogmus, Murat Akçakaya, Suleyman Serdar Kozat, Jan Larsen:
25th IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2015, Boston, MA, USA, September 17-20, 2015. IEEE 2015, ISBN 978-1-4673-7454-5 [contents] - [i1]Corey Kereliuk, Bob L. Sturm, Jan Larsen:
Deep Learning and Music Adversaries. CoRR abs/1507.04761 (2015) - 2014
- [j21]Shigeru Katagiri, Atsushi Nakamura, Tülay Adali, Jianhua Tao, Jan Larsen, Tieniu Tan:
Guest Editorial: Machine Learning for Signal Processing. J. Signal Process. Syst. 74(3): 281-283 (2014) - [c48]Lars Kai Hansen, Søren Holdt Jensen, Jan Larsen:
Preface. CIP 2014: 1 - [c47]Jens Madsen, Bjørn Sand Jensen, Jan Larsen:
Modeling Temporal Structure in Music for Emotion Prediction using Pairwise Comparisons. ISMIR 2014: 319-324 - [c46]Tommy S. Alstrøm, Kasper B. Frohling, Jan Larsen, Mikkel N. Schmidt, Michael Bache, Michael S. Schmidt, Mogens H. Jakobsen, Anja Boisen:
Improving the robustness of Surface Enhanced Raman Spectroscopy based sensors by Bayesian Non-negative Matrix Factorization. MLSP 2014: 1-6 - 2013
- [c45]Bjørn Sand Jensen, Rasmus Troelsgård, Jan Larsen, Lars Kai Hansen:
Towards a universal representation for audio information retrieval and analysis. ICASSP 2013: 3168-3172 - [c44]Bjørn Sand Jensen, Jens Brehm Nielsen, Jan Larsen:
Bounded Gaussian process regression. MLSP 2013: 1-6 - 2012
- [j20]Rasmus G. Haahr, Sune B. Duun, Mette H. Toft, Bo Belhage, Jan Larsen, Karen Birkelund, Erik V. Thomsen:
An Electronic Patch for Wearable Health Monitoring by Reflectance Pulse Oximetry. IEEE Trans. Biomed. Circuits Syst. 6(1): 45-53 (2012) - [c43]Jens Madsen, Bjørn Sand Jensen, Jan Larsen:
Predictive Modeling of Expressed Emotions in Music Using Pairwise Comparisons. CMMR 2012: 253-277 - [c42]Seliz Gulsen Karadogan, Jan Larsen:
Combining semantic and acoustic features for valence and arousal recognition in speech. CIP 2012: 1-6 - [c41]Bjørn Sand Jensen, Javier Saez Gallego, Jan Larsen:
A predictive model of music preference using pairwise comparisons. ICASSP 2012: 1977-1980 - [c40]Tommy S. Alstrøm, Raviv Raich, Natalie V. Kostesha, Jan Larsen:
Feature extraction using distribution representation for colorimetric sensor arrays used as explosives detectors. ICASSP 2012: 2125-2128 - [c39]Tommy S. Alstrøm, Bjørn Sand Jensen, Mikkel N. Schmidt, Natalie V. Kostesha, Jan Larsen:
Haussdorff and hellinger for colorimetric sensor array classification. MLSP 2012: 1-6 - [c38]Jens Brehm Nielsen, Bjørn Sand Jensen, Jan Larsen:
Pseudo inputs for pairwise learning with Gaussian processes. MLSP 2012: 1-6 - [p2]Jan Larsen, Claus Svarer, Lars Nonboe Andersen, Lars Kai Hansen:
Adaptive Regularization in Neural Network Modeling. Neural Networks: Tricks of the Trade (2nd ed.) 2012: 111-130 - 2011
- [j19]Tülay Adali, David J. Miller, Konstantinos I. Diamantaras, Jan Larsen:
Trends in Machine Learning for Signal Processing [In the Spotlight]. IEEE Signal Process. Mag. 28(6): 193-196 (2011) - [j18]Morten Arngren, Mikkel N. Schmidt, Jan Larsen:
Unmixing of Hyperspectral Images using Bayesian Non-negative Matrix Factorization with Volume Prior. J. Signal Process. Syst. 65(3): 479-496 (2011) - [c37]Seliz G. Karadogan, Letizia Marchegiani, Lars Kai Hansen, Jan Larsen:
How efficient is estimation with missing data? ICASSP 2011: 2260-2263 - [c36]Letizia Marchegiani, Seliz G. Karadogan, Tobias Andersen, Jan Larsen, Lars Kai Hansen:
The Role of Top-Down Attention in the Cocktail Party: Revisiting Cherry's Experiment after Sixty Years. ICMLA (1) 2011: 183-188 - [c35]Jakob Eg Larsen, Arkadiusz Stopczynski, Jan Larsen, Claus Vesterskov, Peter Krogsgaard, Thomas Sondrup:
Augmenting the sound experience at music festivals using mobile phones. IUI 2011: 383-386 - [c34]Tommy S. Alstrøm, Jan Larsen, Natalie V. Kostesha, Mogens H. Jakobsen, Anja Boisen:
Data representation and feature selection for colorimetric sensor arrays used as explosives detectors. MLSP 2011: 1-6 - [c33]Bjørn Sand Jensen, Jens Brehm Nielsen, Jan Larsen:
Efficient preference learning with pairwise continuous observations and Gaussian Processes. MLSP 2011: 1-6 - [c32]Seliz G. Karadogan, Letizia Marchegiani, Jan Larsen, Lars Kai Hansen:
Top-down attentionwith features missing at random. MLSP 2011: 1-6 - [c31]Tieniu Tan, Shigeru Katagiri, Jianhua Tao, Atsushi Nakamura, Jan Larsen:
Preface. MLSP 2011: 1 - 2010
- [c30]Seliz Gulsen Karadogan, Jan Larsen, Michael Syskind Pedersen, Jesper Bünsow Boldt:
Robust isolated speech recognition using binary masks. EUSIPCO 2010: 1988-1992 - [c29]Jerónimo Arenas-García, Carlos Moriana-Varo, Jan Larsen:
Combination of recursive supervised and semisupervised filters for improved unbiased estimation. ISWCS 2010: 364-368
2000 – 2009
- 2008
- [j17]Marc M. Van Hulle, Jan Larsen:
Machine Learning for Signal Processing. Neurocomputing 72(1-3): 1-2 (2008) - [j16]Michael Syskind Pedersen, DeLiang Wang, Jan Larsen, Ulrik Kjems:
Two-Microphone Separation of Speech Mixtures. IEEE Trans. Neural Networks 19(3): 475-492 (2008) - 2007
- [j15]Anders Meng, Peter Ahrendt, Jan Larsen, Lars Kai Hansen:
Temporal Feature Integration for Music Genre Classification. IEEE Trans. Speech Audio Process. 15(5): 1654-1664 (2007) - [c28]Lars Kai Hansen, Tue Lehn-Schiøler, Kaare Brandt Petersen, Jerónimo Arenas-García, Jan Larsen, Søren Holdt Jensen:
Learning and clean-up in a large scale music database. EUSIPCO 2007: 946-950 - 2006
- [j14]Anna Szymkowiak-Have, Mark A. Girolami, Jan Larsen:
Clustering via kernel decomposition. IEEE Trans. Neural Networks 17(1): 256-264 (2006) - [j13]Allan Kardec Barros, Danilo P. Mandic, Jan Larsen:
Introductory Note. J. VLSI Signal Process. 45(1-2): 5-6 (2006) - [c27]Michael Syskind Pedersen, Tue Lehn-Schiøler, Jan Larsen:
BLUES from Music: BLind Underdetermined Extraction of Sources from Music. ICA 2006: 392-399 - [c26]Michael Pedersen, DeLiang Wang, Jan Larsen, Ulrik Kjems:
Separating Underdetermined Convolutive Speech Mixtures. ICA 2006: 674-681 - [c25]Lars P. B. Christensen, Jan Larsen:
On Data and Parameter Estimation Using the Variational Bayesian EM-Algorithm for Block-Fading Frequency-Selective MIMO Channels. ICASSP (4) 2006: 465-468 - [c24]Jerónimo Arenas-García, Jan Larsen, Lars Kai Hansen, Anders Meng:
Optimal filtering of dynamics in short-time features for music organization. ISMIR 2006: 290-295 - 2005
- [j12]Marc M. Van Hulle, Jan Larsen:
Neural Networks in Signal Processing. Neurocomputing 69(1-3): 1-2 (2005) - [c23]Michael Syskind Pedersen, Ulrik Kjems, Jan Larsen:
On the difference between updating the mixing matrix and updating the separation matrix. ICASSP (5) 2005: 297-300 - [c22]Anders Meng, Peter Ahrendt, Jan Larsen:
Improving music genre classification by short time feature integration. ICASSP (5) 2005: 497-500 - 2004
- [j11]Sigurdur Sigurdsson, Peter Alshede Philipsen, Lars Kai Hansen, Jan Larsen, Monika Gniadecka, Hans-Christian Wulf:
Detection of skin cancer by classification of Raman spectra. IEEE Trans. Biomed. Eng. 51(10): 1784-1793 (2004) - [j10]David J. Miller, Tülay Adali, Jan Larsen, Marc M. Van Hulle:
Guest Editorial for Special Issue on Machine Learning for Signal Processing. J. VLSI Signal Process. 37(2-3): 171-175 (2004) - [c21]Peter Ahrendt, Anders Meng, Jan Larsen:
Decision time horizon for music genre classification using short time features. EUSIPCO 2004: 1293-1296 - [c20]Rasmus Elsborg Madsen, Sigurdur Sigurdsson, Lars Kai Hansen, Jan Larsen:
Pruning The Vocabulary For Better Context Recognition. ICPR (2) 2004: 483-488 - [c19]Rasmus Elsborg Madsen, Sigurdur Sigurdsson, Lars Kai Hansen, Jan Larsen:
Pruning the vocabulary for better context recognition. IJCNN 2004: 1439-1444 - [c18]Tue Lehn-Schiøler, Lars Kai Hansen, Jan Larsen:
Mapping from Speech to Images Using Continuous State Space Models. MLMI 2004: 136-145 - 2003
- [c17]Joaquin Quiñonero Candela, Agathe Girard, Jan Larsen, Carl Edward Rasmussen:
Propagation of uncertainty in Bayesian kernel models - application to multiple-step ahead forecasting. ICASSP (2) 2003: 701-704 - [c16]Niels Henrik Pontoppidan, Jan Larsen:
Unsupervised condition change detection in large diesel engines. NNSP 2003: 565-574 - 2002
- [j9]Lars Kai Hansen, Finn Årup Nielsen, Jan Larsen:
Exploring fMRI data for periodic signal components. Artif. Intell. Medicine 25(1): 35-44 (2002) - [j8]Ling Guan, Tülay Adali, Shigeru Katagiri, Jan Larsen, José C. Príncipe:
Guest editorial special issue on intelligent multimedia processing. IEEE Trans. Neural Networks 13(4): 789-792 (2002) - [j7]Yu Hen Hu, Jan Larsen:
Guest Editorial. J. VLSI Signal Process. 31(1): 5 (2002) - [j6]Marc M. Van Hulle, Jan Larsen, Tülay Adali:
Guest Editors' Introduction. J. VLSI Signal Process. 32(1-2): 5-6 (2002) - [c15]Sigurdur Sigurdsson, Jan Larsen, Lars Kai Hansen, Peter Alshede Philipsen, Hans-Christian Wulf:
Outlier estimation and detection application to skin lesion classification. ICASSP 2002: 1049-1052 - [c14]Anna Szymkowiak-Have, Jan Larsen, Lars Kai Hansen, Peter Alshede Philipsen, Elisabeth Thieden, Hans-Christian Wulf:
Clustering of Sun exposure measurements. NNSP 2002: 727-735 - [c13]Thomas Kolenda, Lars Kai Hansen, Jan Larsen, Ole Winther:
Independent component analysis for understanding multimedia content. NNSP 2002: 757-766 - 2001
- [c12]Lars Kai Hansen, Jan Larsen, Thomas Kolenda:
Blind detection of independent dynamic components. ICASSP 2001: 3197-3200 - 2000
- [j5]Cyril Goutte, Jan Larsen:
Adaptive Metric Kernel Regression. J. VLSI Signal Process. 26(1-2): 155-167 (2000) - [c11]Lars Kai Hansen, Sigurdur Sigurdsson, Thomas Kolenda, Finn Årup Nielsen, Ulrik Kjems, Jan Larsen:
Modeling text with generalizable Gaussian mixtures. ICASSP 2000: 3494-3497
1990 – 1999
- 1999
- [c10]Lars Nonboe Andersen, Whitlow W. L. Au, Jan Larsen, Lars Kai Hansen:
Sonar discrimination of cylinders from different angles using neural networks. ICASSP 1999: 1121-1124 - 1998
- [j4]Mads Hintz-Madsen, Lars Kai Hansen, Jan Larsen, Morten With Pedersen, Michael Larsen:
Neural classifier construction using regularization, pruning and test error estimation. Neural Networks 11(9): 1659-1670 (1998) - [c9]Cyril Goutte, Jan Larsen:
Adaptive regularization of neural networks using conjugate gradient. ICASSP 1998: 1201-1204 - [c8]Jan Larsen, Lars Nonboe Andersen, Mads Hintz-Madsen, Lars Kai Hansen:
Design of robust neural network classifiers. ICASSP 1998: 1205-1208 - 1997
- [j3]Jan Larsen, Lars Kai Hansen:
Generalization: The Hidden Agenda of Learning. IEEE Signal Process. Mag. 14(6): 43-45 (1997) - [c7]Lars Kai Hansen, Jan Larsen, Torben Fog:
Early stop criterion from the bootstrap ensemble. ICASSP 1997: 3205-3208 - 1996
- [j2]Lars Kai Hansen, Jan Larsen:
Linear unlearning for cross-validation. Adv. Comput. Math. 5(1): 269-280 (1996) - [c6]Lars Kai Hansen, Lars Nonboe Andersen, Ulrik Kjems, Jan Larsen:
Revisiting Boltzmann learning: parameter estimation in Markov random fields. ICASSP 1996: 3394-3397 - [c5]Lars Kai Hansen, Jan Larsen:
Unsupervised learning and generalization. ICNN 1996: 25-30 - [p1]Jan Larsen, Claus Svarer, Lars Nonboe Andersen, Lars Kai Hansen:
Adaptive Regularization in Neural Network Modeling. Neural Networks: Tricks of the Trade 1996: 113-132 - 1995
- [c4]Torben Fog, Jan Larsen, Lars Kai Hansen:
Training and evaluation of neural networks for multi-variate time series processing. ICNN 1995: 1194-1199 - [c3]Morten With Pedersen, Lars Kai Hansen, Jan Larsen:
Pruning with generalization based weight saliencies: gamma-OBD, gamma-OBS. NIPS 1995: 521-527 - [c2]Marian Stewart Bartlett, Paul A. Viola, Terrence J. Sejnowski, Beatrice A. Golomb, Jan Larsen, Joseph C. Hager, Paul Ekman:
Classifying Facial Action. NIPS 1995: 823-829 - 1994
- [j1]Kim Vejlby Hansen, Jan Larsen:
An algorithm for successive identification of reflections. IEEE Trans. Image Process. 3(3): 281-291 (1994) - 1993
- [c1]Claus Svarer, Lars Kai Hansen, Jan Larsen:
On design and evaluation of tapped-delay neural network architectures. ICNN 1993: 46-51
Coauthor Index
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