Algorithmic learning in a random world, 2005. ,
Prediction algorithms and confidence measures based on algorithmic randomness theory, Theoretical Computer Science, vol.287, issue.1, pp.209-217, 2002. ,
DOI : 10.1016/S0304-3975(02)00100-7
URL : http://doi.org/10.1016/s0304-3975(02)00100-7
Hedging Predictions in Machine Learning: The Second Computer Journal Lecture, The Computer Journal, vol.50, issue.2, pp.151-177, 2007. ,
DOI : 10.1093/comjnl/bxl065
Universal Well-Calibrated Algorithm for On-Line Classification, J. Mach. Learn. Res, vol.5, pp.575-604, 2004. ,
DOI : 10.1007/978-3-540-45167-9_27
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.90.7576
Off-line learning with transductive confidence machines: an empirical evaluation, LNAI, pp.310-323, 2007. ,
Regression Conformal Prediction with Nearest Neighbours, J. Artif. Intell. Res, vol.40, pp.815-840, 2011. ,
An online Algorithm with confidence for Real-Time Fault Detection, Journal of Information and Computational Science, vol.6, issue.1, pp.305-313, 2009. ,
Optimized Kernel-Based Conformal Predictor for Online Fault Detection, Journal of Tianjin University, vol.42, issue.7, pp.614-621, 2009. ,
Using random forest for reliable classification and cost-sensitive learning for medical diagnosis, BMC Bioinformatics, vol.10, issue.Suppl 1, p.1, 2009. ,
DOI : 10.1186/1471-2105-10-S1-S22
URL : http://doi.org/10.1186/1471-2105-10-s1-s22
Kernel Learning for Efficiency Maximization in the Conformal Predictions Framework, 2010 Ninth International Conference on Machine Learning and Applications, 2010. ,
DOI : 10.1109/ICMLA.2010.42
Distance Metric Learning for Large Margin Nearest Neighbor Classification, J. Mach. Learn. Res, vol.10, pp.207-244, 2009. ,
Fast discriminative component analysis for comparing examples, Learning to Compare Examples-NIPS 2006 Workshop, p.12, 2006. ,
DOI : 10.1109/mlsp.2007.4414325
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.123.6739
Dimensionality Reduction of Multimodal Labeled Data by Local Fisher Discriminant Analysis, J. Mach. Learn. Res, vol.8, pp.1027-1061, 2007. ,