Tapio Pahikkala
Professor
aatapa@utu.fi +358 29 450 4323 +358 50 345 5824 : 456D |
Machine learning, Data science, Artificial intelligence
Machine learning, Data science, Artificial intelligence
Tapio Pahikkala is a professor of computer science in the University of Turku, Finland, from which he also received his doctoral degree in 2008. He has authored more than 150 peer-reviewed scientific articles and participated in the winning teams of several international scientific competitions/challenges. He has led many research projects, supervised more than ten doctoral theses, held several positions of trust in academia and served in the program committees of numerous international conferences. His current research interests include theory and algorithmics of machine learning, data analysis, and artificial intelligence, as well as their applications on various different fields.
Theory and algorithmics of machine learning, data science and artificial intelligence as well as their practical applications in various different fields. Estimation of prediction performance with resampling methods, theory of resampling and cross-validation.
TKO_7092 Evaluation of Machine Learning Methods
- Fuzzy Logic Based Control for Parallel Cascade Control (2010)
- International Journal on Automatic Control and System Engineering
- Greedy {RankRLS}: a Linear Time Algorithm for Learning Sparse Ranking Models (2010) SIGIR 2010 Workshop on Feature Generation and Selection for Information Retrieval Pahikkala T, Airola A, Naula P, Salakoski T
- Large scale training methods for linear {RankRLS} (2010) Proceedings of the {ECML/PKDD} 2010 Workshop on Preference Learning {(PL-10)} Airola A, Pahikkala T, Salakoski T
- Learning Intransitive Reciprocal Relations with Kernel Methods (2010)
- European Journal of Operational Research
- Proceedings of the 14th Finnish Artificial Intelligence Conference, STeP 2010 (2010) Pahikkala T, Väyrynen J, Kortela J, Airola A (eds. )
- Speeding up Greedy Forward Selection for Regularized Least-Squares (2010) Proceedings of The Ninth International Conference on Machine Learning and Applications (ICMLA 2010) Pahikkala T, Airola A, Salakoski T
- An efficient algorithm for learning to rank from preference graphs (2009)
- Machine Learning
- Efficient Hold-Out for Subset of Regressors (2009)
- Lecture Notes in Computer Science
- Extracting Complex Biological Events with Rich Graph-Based Feature Sets (2009) Proceedings of the BioNLP 2009 Workshop Companion Volume for Shared Task Björne J, Heimonen J, Ginter F, Airola A, Pahikkala T, Salakoski T
- Locality kernels for sequential data and their applications to parse ranking (2009)
- Applied Intelligence
