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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
32762004
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
3942005
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
3362006
The 2005 pascal visual object classes challenge
M Everingham, A Zisserman, CKI Williams, LV Gool, M Allan, CM Bishop, ...
Machine Learning Challenges Workshop, 117-176, 2005
3292005
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
2771998
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
2472000
Improving" bag-of-keypoints" image categorisation: Generative models and pdf-kernels
J Farquhar, S Szedmak, H Meng, J Shawe-Taylor
1652005
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
1222005
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
1191995
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
1132004
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
Severity of allergic complaints: the importance of depressed mood
M Kovács, A Stauder, S Szedmák
Journal of psychosomatic research 54 (6), 549-557, 2003
652003
Kernel-mapping recommender system algorithms
MA Ghazanfar, A Prügel-Bennett, S Szedmak
Information Sciences 208, 81-104, 2012
622012
Towards structured output prediction of enzyme function
K Astikainen, L Holm, E Pitkänen, S Szedmak, J Rousu
BMC proceedings 2 (4), 1-10, 2008
592008
Learning via linear operators: Maximum margin regression
S Szedmak, J Shawe-Taylor
In Proceedings of 2001 IEEE International Conference on Data Mining, 2005
462005
Liquid-chromatography retention order prediction for metabolite identification
E Bach, S Szedmak, C Brouard, S Böcker, J Rousu
Bioinformatics 34 (17), i875-i883, 2018
452018
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
442018
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
401998
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), 1-11, 2020
352020
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
341997
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Articles 1–20