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Sandor Szedmak
Sandor Szedmak
Department of Computer Science, Aalto University
Verified email at aalto.fi
Title
Cited by
Cited by
Year
Canonical correlation analysis: An overview with application to learning methods
DR Hardoon, S Szedmak, J Shawe-Taylor
Neural computation 16 (12), 2639-2664, 2004
37662004
Two view learning: SVM-2K, theory and practice
J Farquhar, D Hardoon, H Meng, J Shawe-Taylor, S Szedmak
Advances in neural information processing systems 18, 2005
4302005
Kernel-based learning of hierarchical multilabel classification models
J Rousu, C Saunders, S Szedmak, J Shawe-Taylor
Journal of Machine Learning Research 7, 1601-1626, 2006
3702006
The 2005 pascal visual object classes challenge
M Everingham, A Zisserman, CKI Williams, L Van Gool, M Allan, ...
Machine Learning Challenges. Evaluating Predictive Uncertainty, Visual …, 2006
3692006
Depressive symptomatology and vital exhaustion are differentially related to behavioral risk factors for coronary artery disease
MS Kopp, PRJ Falger, AD Appels, S Szedmak
Psychosomatic medicine 60 (6), 752-758, 1998
2961998
Psychosocial risk factors, inequality and self-rated morbidity in a changing society
MS Kopp, Á Skrabski, S Szedmák
Social science & medicine 51 (9), 1351-1361, 2000
2662000
Improving" bag-of-keypoints" image categorisation: Generative models and pdf-kernels
J Farquhar, S Szedmak, H Meng, J Shawe-Taylor
1662005
Learning hierarchical multi-category text classification models
J Rousu, C Saunders, S Szedmak, J Shawe-Taylor
Proceedings of the 22nd international conference on Machine learning, 744-751, 2005
1242005
Pareto-Optimal Patterns in Logical Analysis of Data
SS P.L. Hammer, A. Kogan, B. Simeone
Discrete Applied Mathematics 144 (1-2), 79-102, 2004
1212004
Socioeconomic factors, severity of depressive symptomatology, and sickness absence rate in the Hungarian population
MS Kopp, Á Skrabski, S Szedmák
Journal of Psychosomatic Research 39 (8), 1019-1029, 1995
1211995
Learning with multiple pairwise kernels for drug bioactivity prediction
A Cichonska, T Pahikkala, S Szedmak, H Julkunen, A Airola, M Heinonen, ...
Bioinformatics 34 (13), i509-i518, 2018
732018
Leveraging multi-way interactions for systematic prediction of pre-clinical drug combination effects
H Julkunen, A Cichonska, P Gautam, S Szedmak, J Douat, T Pahikkala, ...
Nature communications 11 (1), 6136, 2020
722020
Liquid-chromatography retention order prediction for metabolite identification
E Bach, S Szedmak, C Brouard, S Böcker, J Rousu
Bioinformatics 34 (17), i875-i883, 2018
712018
Severity of allergic complaints: the importance of depressed mood
M Kovács, A Stauder, S Szedmák
Journal of psychosomatic research 54 (6), 549-557, 2003
712003
Kernel-mapping recommender system algorithms
MA Ghazanfar, A Prügel-Bennett, S Szedmak
Information Sciences 208, 81-104, 2012
692012
A correlation approach for automatic image annotation
DR Hardoon, C Saunders, S Szedmak, J Shawe-Taylor
International Conference on Advanced Data Mining and Applications, 681-692, 2006
692006
Towards structured output prediction of enzyme function
K Astikainen, L Holm, E Pitkänen, S Szedmak, J Rousu
BMC proceedings 2, 1-10, 2008
602008
Learning via linear operators: Maximum margin regression
S Szedmak, J Shawe-Taylor, E Parado-Hernandez
In Proceedings of 2001 IEEE International Conference on Data Mining. Citeseer, 2005
462005
Socioeconomic differences and psychosocial aspects of stress in a changing society
MS Kopp, S Szedmák, A Skrabski
ANNALS-NEW YORK ACADEMY OF SCIENCES 851, 538-543, 1998
391998
A depressziós tünetegyüttes gyakorisága és egészségügyi jelentősége a magyar lakosság körében
M Kopp, S Szedmák, J Lőke, Á Skrabski
Lege Artis Med 3, 136-44, 1997
361997
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Articles 1–20