Antti Airola

发表

Computational-experimental approach to drug-target interaction mapping: A case study on kinase inhibitors

Juho Rousu, Anna Cichonska, Balaguru Ravikumar, 2017, PLoS Comput. Biol..

Algebraic Shortcuts for Leave-One-Out Cross-Validation in Supervised Network Inference

Tapio Pahikkala, Antti Airola, Michiel Stock, 2018, bioRxiv.

Modelling user retention in mobile games

Jukka Heikkonen, Tapio Pahikkala, Antti Airola, 2016, 2016 IEEE Conference on Computational Intelligence and Games (CIG).

Conditional Ranking on Relational Data

Tapio Salakoski, Bernard De Baets, Tapio Pahikkala, 2010, ECML/PKDD.

Training linear ranking SVMs in linearithmic time using red-black trees

Tapio Salakoski, Tapio Pahikkala, Antti Airola, 2010, Pattern Recognit. Lett..

On Learning and Cross-Validation with Decomposed Nyström Approximation of Kernel Matrix

Tapio Salakoski, Tapio Pahikkala, Antti Airola, 2011, Neural Processing Letters.

A comparison of AUC estimators in small-sample studies

Tapio Salakoski, Bernard De Baets, Tapio Pahikkala, 2009, MLSB.

The spatial leave-pair-out cross-validation method for reliable AUC estimation of spatial classifiers

Jukka Heikkonen, Tapio Pahikkala, Antti Airola, 2018, Data Mining and Knowledge Discovery.

EXTRACTING CONTEXTUALIZED COMPLEX BIOLOGICAL EVENTS WITH RICH GRAPH‐BASED FEATURE SETS

Jari Björne, Tapio Salakoski, Juho Heimonen, 2011, Comput. Intell..

Generalized vec trick for fast learning of pairwise kernel models pdf

Tapio Pahikkala, Antti Airola, Markus Viljanen, 2020, ArXiv.

A Parallel Online Regularized Least-squares Machine Learning Algorithm for Future Multi-core Processors

Tapio Salakoski, Hannu Tenhunen, Thomas Canhao Xu, 2011, PECCS.

An efficient algorithm for learning to rank from preference graphs

Tapio Pahikkala, Antti Airola, Jouni Järvinen, 2009, Machine Learning.

Synthetic minority oversampling of vital statistics data with generative adversarial networks

Tapio Pahikkala, Antti Airola, Aki Koivu, 2020, J. Am. Medical Informatics Assoc..

Comparative analysis of five protein-protein interaction corpora

Jari Björne, Tapio Salakoski, Juho Heimonen, 2008, BMC Bioinformatics.

Fast Kronecker product kernel methods via sampled vec trick pdf

Tapio Pahikkala, Antti Airola, T. Pahikkala, 2016, ArXiv.

Spectral Analysis of Symmetric and Anti-Symmetric Pairwise Kernels pdf

Tapio Pahikkala, Antti Airola, Willem Waegeman, 2015, ArXiv.

Efficient Pairwise Learning Using Kernel Ridge Regression: an Exact Two-Step Method pdf

Bernard De Baets, Tapio Pahikkala, Antti Airola, 2016, ArXiv.

Learning Multi-Label Predictors under Sparsity Budget

Tapio Salakoski, Tapio Pahikkala, Antti Airola, 2011, SCAI.

Fast Kronecker Product Kernel Methods via Generalized Vec Trick

Tapio Pahikkala, Antti Airola, T. Pahikkala, 2016, IEEE Transactions on Neural Networks and Learning Systems.

Extracting Complex Biological Events with Rich Graph-Based Feature Sets

Jari Björne, Tapio Salakoski, Juho Heimonen, 2009, BioNLP@HLT-NAACL.

A Two-Step Learning Approach for Solving Full and Almost Full Cold Start Problems in Dyadic Prediction

Bernard De Baets, Tapio Pahikkala, Antti Airola, 2014, ECML/PKDD.

Fast and simple gradient-based optimization for semi-supervised support vector machines

Oliver Kramer, Tapio Pahikkala, Antti Airola, 2014, Neurocomputing.

An experimental comparison of cross-validation techniques for estimating the area under the ROC curve

Tapio Salakoski, Bernard De Baets, Tapio Pahikkala, 2011, Comput. Stat. Data Anal..

A kernel framework for learning relations from paired-comparison data

Tapio Salakoski, Bernard De Baets, Tapio Pahikkala, 2011 .

Wrapper-based selection of genetic features in genome-wide association studies through fast matrix operations

Tapio Salakoski, Tapio Pahikkala, Antti Airola, 2012, Algorithms for Molecular Biology.

Efficient regularized least-squares algorithms for conditional ranking on relational data

Bernard De Baets, Tapio Pahikkala, Antti Airola, 2012, Machine Learning.

A Comparative Study of Pairwise Learning Methods Based on Kernel Ridge Regression

Bernard De Baets, Tapio Pahikkala, Antti Airola, 2018, Neural Computation.

Efficient AUC Maximization with Regularized Least-Squares

Tapio Salakoski, Tapio Pahikkala, Antti Airola, 2008, SCAI.

Kernel-Based Ranking. Methods for Learning and Performance Estimation

Antti Airola, 2011 .

User activity decay in mobile games determined by simple differential equations?

Jukka Heikkonen, Tapio Pahikkala, Antti Airola, 2016, 2016 IEEE Conference on Computational Intelligence and Games (CIG).

Comparison of automatic summarisation methods for clinical free text notes

Tapio Salakoski, Juho Heimonen, Sanna Salanterä, 2016, Artif. Intell. Medicine.

Toward more realistic drug^target interaction predictions

Tapio Pahikkala, Antti Airola, Tero Aittokallio, 2014 .

Statistical parsing of varieties of clinical Finnish

Tapio Salakoski, Veronika Laippala, Sanna Salanterä, 2014, Artif. Intell. Medicine.

Identification of Functionally Related Enzymes by Learning-to-Rank Methods

Eyke Hüllermeier, Gerhard Klebe, Bernard De Baets, 2014, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Conditional ranking algorithms for efﬁcient object retrieval and object querying on relational data

Tapio Salakoski, Bernard De Baets, Tapio Pahikkala, 2012 .

Fast and parallelized greedy forward selection of genetic variants in Genome-wide association studies

Tapio Salakoski, Tapio Pahikkala, Antti Airola, 2011, 2011 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS).

Learning Valued Relations from Data

Tapio Salakoski, Bernard De Baets, Tapio Pahikkala, 2011, Eurofuse.

Speedy Local Search for Semi-Supervised Regularized Least-Squares

Oliver Kramer, Tapio Pahikkala, Antti Airola, 2011, KI.

Algebraic shortcuts for leave-one-out cross-validation in supervised network inference

Bernard De Baets, Tapio Pahikkala, Antti Airola, 2020, Briefings Bioinform..

A Sparse Regularized Least-Squares Preference Learning Algorithm

Tapio Salakoski, Tapio Pahikkala, Antti Airola, 2008, SCAI.

On Evaluation of Automatically Generated Clinical Discharge Summaries

Tapio Salakoski, Juho Heimonen, Laura-Maria Murtola, 2014, PAHI.

Cost-effective survival prediction for patients with advanced prostate cancer using clinical trial and real-world hospital registry datasets

Tapio Pahikkala, Antti Airola, Tero Aittokallio, 2019, Int. J. Medical Informatics.

Applying Permutation Tests for Assessing the Statistical Significance of Wrapper Based Feature Selection

Tapio Salakoski, Tapio Pahikkala, Antti Airola, 2010, 2010 Ninth International Conference on Machine Learning and Applications.

Speeding Up Greedy Forward Selection for Regularized Least-Squares

Tapio Salakoski, Tapio Pahikkala, Antti Airola, 2010, 2010 Ninth International Conference on Machine Learning and Applications.

Playtime Measurement With Survival Analysis

Tapio Pahikkala, Antti Airola, Jukka Heikkonen, 2017, IEEE Transactions on Games.

Implementation and Analysis of Block Dense Matrix Decomposition on Network-on-Chips

Tapio Salakoski, Hannu Tenhunen, Thomas Canhao Xu, 2012, 2012 IEEE 14th International Conference on High Performance Computing and Communication & 2012 IEEE 9th International Conference on Embedded Software and Systems.

A Low-Overhead, Fully-Distributed, Guaranteed-Delivery Routing Algorithm for Faulty Network-on-Chips

Hannu Tenhunen, Siamak Mohammadi, Pasi Liljeberg, 2015, NOCS.

Greedy Regularized Least-Squares for Multi-task Learning

Tapio Salakoski, Tapio Pahikkala, Antti Airola, 2011, 2011 IEEE 11th International Conference on Data Mining Workshops.

Learning with multiple pairwise kernels for drug bioactivity prediction

Juho Rousu, Anna Cichonska, Tapio Pahikkala, 2018, Bioinform..

Measuring Player Retention and Monetization Using the Mean Cumulative Function

Tapio Pahikkala, Antti Airola, Jukka Heikkonen, 2017, IEEE Transactions on Games.

Efficient recurrent local search strategies for semi- and unsupervised regularized least-squares classification

Oliver Kramer, Tapio Pahikkala, Antti Airola, 2012, Evol. Intell..

Learning Low Cost Multi-target Models by Enforcing Sparsity

Tapio Salakoski, Tapio Pahikkala, Antti Airola, 2015, IEA/AIE.

Parallelized Online Regularized Least-Squares for Adaptive Embedded Systems

Tapio Salakoski, Hannu Tenhunen, Thomas Canhao Xu, 2012, Int. J. Embed. Real Time Commun. Syst..

Tournament leave-pair-out cross-validation for receiver operating characteristic analysis

Tapio Pahikkala, Antti Airola, Ivan Jambor, 2018, Statistical methods in medical research.

An Improved Training Algorithm for the Linear Ranking Support Vector Machine

Tapio Salakoski, Tapio Pahikkala, Antti Airola, 2011, ICANN.

Propagating AI Knowledge Across University Disciplines- The Design of A Multidisciplinary AI Study Module

Tapio Salakoski, Antti Airola, Ali Farooq, 2020, 2020 IEEE Frontiers in Education Conference (FIE).

O-CDIO: emphasizing design Thinking in CDIO engineering cycle

Tapio Salakoski, Tapio Pahikkala, Antti Airola, 2016 .

A/B-Test of Retention and Monetization Using the Cox Model

Jukka Heikkonen, Tapio Pahikkala, Antti Airola, 2017, AIIDE.

Drug-Drug Interaction Extraction from Biomedical Texts with SVM and RLS Classifiers

Tapio Salakoski, Tapio Pahikkala, Antti Airola, 2011 .

On Unsupervised Training of Multi-Class Regularized Least-Squares Classifiers

Oliver Kramer, Tapio Pahikkala, Antti Airola, 2014, Journal of Computer Science and Technology.

Learning monadic and dyadic relations : three case studies in systems biology

Tapio Salakoski, Bernard De Baets, Tapio Pahikkala, 2012 .

On parallel online learning for adaptive embedded systems

Tapio Salakoski, Hannu Tenhunen, Thomas Canhao Xu, 2014 .

Predicting patient acuity from electronic patient records

Tapio Salakoski, Heljä Lundgrén-Laine, Sanna Salanterä, 2014, J. Biomed. Informatics.

Parallel Feature Selection for Regularized Least-Squares

Tapio Salakoski, Tapio Pahikkala, Antti Airola, 2012, PARA.

Sparse Quasi-Newton Optimization for Semi-supervised Support Vector Machines

Oliver Kramer, Tapio Pahikkala, Antti Airola, 2012, ICPRAM.

Multi-label learning under feature extraction budgets

Tapio Salakoski, Tapio Pahikkala, Antti Airola, 2014, Pattern Recognit. Lett..

AI in Cybersecurity Education- A Systematic Literature Review of Studies on Cybersecurity MOOCs

Antti Airola, Ali Farooq, Antti Hakkala, 2020, 2020 IEEE 20th International Conference on Advanced Learning Technologies (ICALT).

A general-purpose toolbox for efficient Kronecker-based learning

Bernard De Baets, Tapio Pahikkala, Antti Airola, 2020 .

A Kernel-Based Framework for Learning Graded Relations From Data

Tapio Salakoski, Bernard De Baets, Tapio Pahikkala, 2011, IEEE Transactions on Fuzzy Systems.

RLScore: Regularized Least-Squares Learners

Tapio Pahikkala, Antti Airola, 2016, J. Mach. Learn. Res..

Unsupervised Multi-class Regularized Least-Squares Classification

Oliver Kramer, Tapio Pahikkala, Antti Airola, 2012, 2012 IEEE 12th International Conference on Data Mining.

Robust ECG R-peak detection using LSTM

Mingzhe Jiang, Nikil D. Dutt, Pasi Liljeberg, 2020, SAC.

A Graph Kernel for Protein-Protein Interaction Extraction

Jari Björne, Tapio Salakoski, Sampo Pyysalo, 2008, BioNLP.

Training neural networks with synthetic electrocardiograms pdf

Antti Airola, Matti Kaisti, Juho Laitala, 2021, ArXiv.

A Link between Coding Theory and Cross-Validation with Applications pdf

Tapio Pahikkala, Antti Airola, Ivan Jambor, 2021, ArXiv.

Adaptive risk prediction system with incremental and transfer learning

Tapio Pahikkala, Antti Airola, Aki Koivu, 2021, Comput. Biol. Medicine.

EXACT AND EFFICIENT LEAVE-PAIR-OUT CROSS-VALIDATION FOR RANKING RLS

Tapio Salakoski, Tapio Pahikkala, Antti Airola, 2008 .

Large scale training methods for linear RankRLS

Tapio Salakoski, Tapio Pahikkala, Antti Airola, 2010 .

Feature selection for regularized least-squares: New computational short-cuts and fast algorithmic implementations

Tapio Salakoski, Tapio Pahikkala, Antti Airola, 2010, 2010 IEEE International Workshop on Machine Learning for Signal Processing.

Prediction of overall survival for patients with metastatic castration-resistant prostate cancer: development of a prognostic model through a crowdsourced challenge with open clinical trial data.

Thomas Yu, Tapio Pahikkala, Antti Airola, 2017, The Lancet. Oncology.