 | 2012 |
| 20 |  | Fabian Gieseke,
Antti Airola,
Tapio Pahikkala,
Oliver Kramer:
Sparse Quasi-Newton Optimization for Semi-supervised Support Vector Machines.
ICPRAM (1) 2012: 45-54 |
| 2011 |
| 19 |  | Antti Airola,
Tapio Pahikkala,
Tapio Salakoski:
An Improved Training Algorithm for the Linear Ranking Support Vector Machine.
ICANN (1) 2011: 134-141 |
| 18 |  | Pekka Naula,
Tapio Pahikkala,
Antti Airola,
Tapio Salakoski:
Greedy Regularized Least-Squares for Multi-task Learning.
ICDM Workshops 2011: 527-533 |
| 17 |  | Fabian Gieseke,
Oliver Kramer,
Antti Airola,
Tapio Pahikkala:
Speedy Local Search for Semi-Supervised Regularized Least-Squares.
KI 2011: 87-98 |
| 16 |  | Tapio Pahikkala,
Antti Airola,
Thomas Canhao Xu,
Pasi Liljeberg,
Hannu Tenhunen,
Tapio Salakoski:
A Parallel Online Regularized Least-squares Machine Learning Algorithm for Future Multi-core Processors.
PECCS 2011: 590-599 |
| 15 |  | Pekka Naula,
Tapio Pahikkala,
Antti Airola,
Tapio Salakoski:
Learning Multi-Label Predictors under Sparsity Budget.
SCAI 2011: 30-39 |
| 14 |  | Willem Waegeman,
Tapio Pahikkala,
Antti Airola,
Tapio Salakoski,
Michiel Stock,
Bernard De Baets:
A kernel-based framework for learning graded relations from data
CoRR abs/1111.6473: (2011) |
| 13 |  | Jari Björne,
Juho Heimonen,
Filip Ginter,
Antti Airola,
Tapio Pahikkala,
Tapio Salakoski:
Extracting Contextualized Complex Biological Events with Rich Graph-Based Feature Sets.
Computational Intelligence 27(4): 541-557 (2011) |
| 12 |  | Antti Airola,
Tapio Pahikkala,
Willem Waegeman,
Bernard De Baets,
Tapio Salakoski:
An experimental comparison of cross-validation techniques for estimating the area under the ROC curve.
Computational Statistics & Data Analysis 55(4): 1828-1844 (2011) |
| 11 |  | Antti Airola,
Tapio Pahikkala,
Tapio Salakoski:
On Learning and Cross-Validation with Decomposed Nyström Approximation of Kernel Matrix.
Neural Processing Letters 33(1): 17-30 (2011) |
| 10 |  | Antti Airola,
Tapio Pahikkala,
Tapio Salakoski:
Training linear ranking SVMs in linearithmic time using red-black trees.
Pattern Recognition Letters 32(9): 1328-1336 (2011) |
| 2010 |
| 9 |  | Tapio Pahikkala,
Willem Waegeman,
Antti Airola,
Tapio Salakoski,
Bernard De Baets:
Conditional Ranking on Relational Data.
ECML/PKDD (2) 2010: 499-514 |
| 8 |  | Tapio Pahikkala,
Antti Airola,
Tapio Salakoski:
Speeding Up Greedy Forward Selection for Regularized Least-Squares.
ICMLA 2010: 325-330 |
| 7 |  | Antti Airola,
Tapio Pahikkala,
Jorma Boberg,
Tapio Salakoski:
Applying Permutation Tests for Assessing the Statistical Significance of Wrapper Based Feature Selection.
ICMLA 2010: 989-994 |
| 6 |  | Antti Airola,
Tapio Pahikkala,
Willem Waegeman,
Bernard De Baets,
Tapio Salakoski:
A comparison of AUC estimators in small-sample studies.
Journal of Machine Learning Research - Proceedings Track 8: 3-13 (2010) |
| 2009 |
| 5 |  | Tapio Pahikkala,
Evgeni Tsivtsivadze,
Antti Airola,
Jouni Järvinen,
Jorma Boberg:
An efficient algorithm for learning to rank from preference graphs.
Machine Learning 75(1): 129-165 (2009) |
| 2008 |
| 4 |  | Tapio Pahikkala,
Antti Airola,
Hanna Suominen,
Jorma Boberg,
Tapio Salakoski:
Efficient AUC Maximization with Regularized Least-Squares.
SCAI 2008: 12-19 |
| 3 |  | Evgeni Tsivtsivadze,
Tapio Pahikkala,
Antti Airola,
Jorma Boberg,
Tapio Salakoski:
A Sparse Regularized Least-Squares Preference Learning Algorithm.
SCAI 2008: 76-83 |
| 2 |  | Antti Airola,
Sampo Pyysalo,
Jari Björne,
Tapio Pahikkala,
Filip Ginter,
Tapio Salakoski:
All-paths graph kernel for protein-protein interaction extraction with evaluation of cross-corpus learning.
BMC Bioinformatics 9(S-11): (2008) |
| 1 |  | Sampo Pyysalo,
Antti Airola,
Juho Heimonen,
Jari Björne,
Filip Ginter,
Tapio Salakoski:
Comparative analysis of five protein-protein interaction corpora.
BMC Bioinformatics 9(S-3): (2008) |