| 2014 |
| G. Takács, Predicting flight arrival times with a multistage model, Proc. of 2014 IEEE Conference on BigData (IEEE BigData 2014), Workshop on Large Data Analytics in Transportation Engineering, p. 78-84, Washington DC, USA, 2014. [pdf] |
| C. Kiss-Tóth, G. Takács, A dynamic programming approach for 4D flight route optimization, Proc. of 2014 IEEE Conference on BigData (IEEE BigData 2014), Workshop on Large Data Analytics in Transportation Engineering, p. 24-28, Washington DC, USA, 2014. [pdf] |
| 2013 |
| B. Németh, G. Takács, I. Pilászy, D. Tikk, Visualization of movie features in collaborative filtering, Proc. of the 12th IEEE International Conference on Intelligent Software Methodologies, Tools and Techniques (SoMeT 2013), p. 229-233, Budapest, Hungary, 2013. |
| 2012 |
| G. Takács, D. Tikk, Alternating least squares for personalized ranking, received Honorable Mention at 6th ACM Conference on Recommender Systems (RecSys 2012), Dublin, Ireland, 2012. [pdf] [erratum] |
| Z. Horváth, T. A. Kocsis, G. Takács, L. Komzsik, Development of a virtual wind tunnel, Proc. of the 9th International Symposium on Tools and Methods of Competitive Engineering (TMCE 2012), p. 1147-1156, Karlsruhe, Germany, 2012. |
| 2011 |
| G. Takács, I. Pilászy, D. Tikk, Applications of the conjugate gradient method for implicit feedback collaborative filtering, 5th ACM Conference on Recommender Systems (RecSys 2011), Chicago, Illinois, USA, 2011. [pdf] |
| G. Takács, Z. Horváth, GPU parallel 3D Euler flow simulation on unstructured polyhedral meshes, Conference on Simulation and Optimization, Győr, Hungary, 2011. |
| O. Horváth, G. Takács, Predictor set optimization for collaborative filtering, Proc. of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems (IDAACS'2011), p. 404-407, Prague, Czech Republic, 2011. |
| 2010 |
| G. Takács, Z. Horváth, G. Veres, Fast tomographic reconstruction on parallel hardware, 8th International Conference on Numerical Analysis and Applied Mathematics (ICNAAM 2010), Rhodes, Greece, 2010. [pdf] |
| G. Takács, Convex polyhedron learning and its applications, PhD thesis, Budapest University of Technology and Economics, Faculty of Electrical Engineering and Informatics, Budapest, Hungary, 2010. [pdf] |
| G. Takács, Smooth maximum function based algorithms for classification, regression, and collaborative filtering, Acta Technica Jaurinensis, Series Computatorica Intelligentica, 3(1): 27-63, 2010. |
| G. Takács, Gaussian transductive regression, Veszprém Optimization Conference: Advanced Algorithms (VOCAL 2010), Veszprém, Hungary, 2010. |
| 2009 |
| G. Takács, I. Pilászy, B. Németh, D. Tikk, Scalable collaborative filtering approaches for large recommender systems, Journal of Machine Learning Research (Special Topic on Mining and Learning with Graphs and Relations), 10: 623-656, 2009. [pdf] |
| J. Sill, G. Takács, L. Mackey, D. Lin, Feature-weighted linear stacking, arXiv:0911.0460v2, 2009. [pdf] |
| G. Takács, Efficient algorithms for determining the linear and convex separability of point sets, Acta Technica Jaurinensis, Series Computatorica Intelligentica, vol. 2., no. 2, pp. 287-310, 2009. |
| G. Takács, The smooth maximum classifier, Abstracts of the 2nd Győr Symposium on Computational Intelligence, p. 34-36, Győr, Hungary, 2009. |
| R. Horváth-Bokor, Z. Horváth, G. Takács, (in Hungarian), Kockázatelemzés logisztikus regresszióval nagy adathalmazokon, 28. Magyar Operációkutatási Konferencia, Balatonőszöd, Hungary, 2009. |
| 2008 |
| G. Takács, I. Pilászy, B. Németh, D. Tikk, Matrix factorization and neighbor based algorithms for the Netflix Prize problem, Proc. of the 2nd ACM Conference on Recommender Systems (RecSys 2008), p. 267-274, Lausanne, Switzerland, 2008. |
| G. Takács, I. Pilászy, B. Németh, D. Tikk, Investigation of various matrix factorization methods for large recommender systems, Proc. of the 2nd KDD Workshop on Large Scale Recommender Systems and the Netflix Prize Competition, Las Vegas, Nevada, USA, 2008. [pdf] |
| G. Takács, I. Pilászy, B. Németh, D. Tikk, A unified approach of factor models and neighbor based methods for large recommender systems, Proc. of the 1th IEEE ICADIWT Workshop on Recommender Systems and Personalized Retrieval, p. 186-191, Ostrava, Czech Republic, 2008. [pdf] |
| G. Takács, I. Pilászy, B. Németh, D. Tikk, Unifying collaborative filtering approaches, Veszprém Optimization Conference: Advanced Algorithms (VOCAL 2008), Veszprém, Hungary, 2008. |
| 2007 |
| G. Takács, I. Pilászy, B. Németh, D. Tikk, Major components of the Gravity Recommendation System, ACM SIGKDD Explorations Newsletter, 9(2): 80-83, 2007. [pdf] |
| G. Takács, I. Pilászy, B. Németh, D. Tikk, On the Gravity Recommendation System, Proc. of the KDD Cup and Workshop 2007, p. 22-30, San Jose, California, USA, 2007. [pdf] |
| G. Takács and B. Pataki, Case-level detection of mammographic masses, International Journal of Applied Electromagnetics and Mechanics, 25(1-4): 395-400, 2007. |
| G. Takács, The Vapnik-Chervonenkis dimension of convex n-gon classifiers, Hungarian Electronic Journal of Sciences, 2007. |
| G. Takács, B. Pataki, Lower bounds on the Vapnik-Chervonenkis dimension of convex polytope classifiers, Proc. of the 11th International Conference on Intelligent Engineering Systems (INES 2007), Budapest, Hungary, 2007. |
| G. Takács, B. Pataki, Deciding the convex separability of pattern sets, Proc. of the 4th IEEE Workshop on Intelligent Data Acquisition and Advanced Computing Systems (IDAACS'2007), Dortmund, Germany, 2007. |
| G. Takács, B. Pataki, An efficient algorithm for deciding the convex separability of point sets, Proc. of the 14th PhD Mini-Symposium, Budapest University of Technology and Economics, Department of Measurement and Information Systems, pp. 54-57, Budapest, Hungary, 2007. |
| G. Takács, B. Pataki, Nearest local hyperplane rules for pattern classification, AI*IA 2007: Artificial Intelligence and Human-Oriented Computing, pp. 302-313, Rome, Italy, 2007. |
| G. Takács, B. Pataki, (in Hungarian), A lépcsőzetes döntéshozás elvének műszaki alkalmazásai, Elektronet, 16(8): 76-78, 2007. |
| 2006 |
| M. Altrichter, G. Horváth, B. Pataki, Gy. Strausz, G. Takács and J. Valyon, (in Hungarian), Neurális hálózatok, Panem, 2006. |
| G. Takács and B. Pataki, Local hyperplane classifiers, Proc. of the 13th PhD Mini-Symposium, Budapest University of Technology and Economics, Department of Measurement and Information Systems, p. 44-45, Budapest, Hungary, 2006. |
| 2005 |
| G. Takács, B. Pataki, Fast detection of masses in mammograms with difficult case exclusion, International Scientific Journal of Computing, 4(3): 70-75, 2005. |
| G. Takács, B. Pataki, Case-level detection of mammographic masses, Proc. of the 12th International Symposium on Interdisciplinary Electromagnetic, Mechanic and Biomedical Problems (ISEM 2005), p. 214-215, Bad Gastein, Austria, 2005. |
| G. Takács, B. Pataki, Fast detection of mammographic masses with difficult case exclusion, Proc. of the 3rd IEEE Workshop on Intelligent Data Acquisition and Advanced Computing Systems (IDAACS'2005), p. 424-428, Sofia, Bulgaria, 2005. |
| G. Takács, B. Pataki, Computer-aided detection of mammographic masses, Proc. of the 12th PhD Mini-Symposium, Budapest University of Technology and Economics, Department of Measurement and Information Systems, p. 24-25, Budapest, Hungary, 2005. |
| N. Tóth, G. Takács, B. Pataki, Mass detection in mammograms combining two methods, Proc. of the 3rd European Medical & Biological Engineering Conference (EMBEC'05), Prague, Czech Republic, 2005. |
| G. Horváth, B. Pataki, Á. Horváth, G. Takács, G. Balogh, Detection of microcalcification clusters in screening mammography, Proc. of the 3rd European Medical & Biological Engineering Conference (EMBEC'05), Prague, Czech Republic, 2005. |