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Ridge Regression Learning Algorithm in Dual Variables
- C. Saunders, A. Gammerman, V. Vovk
- Computer ScienceInternational Conference on Machine Learning
- 24 July 1998
A regression estimation algorithm which is a combination of the dual version of Ridge Regression is applied to the ANOVA enhancement of the infinitenode splines and the use of kernel functions, as used in Support Vector methods is introduced.
A tutorial on conformal prediction
This tutorial presents a self-contained account of the theory of conformal prediction and works through several numerical examples of how the model under which successive examples are sampled independently from the same distribution can be applied to any method for producing ŷ.
Aggregating strategies
- V. Vovk
- Computer ScienceAnnual Conference Computational Learning Theory
- 1 July 1990
A game of prediction with expert advice
- V. Vovk
- Computer ScienceAnnual Conference Computational Learning Theory
- 5 July 1995
We consider the following problem. At each point of discrete time the learner must make a prediction; he is given the predictions made by a pool of experts. Each prediction and the outcome, which is…
Probability and Finance: It's Only a Game!
Preface. Probability and Finance as a Game. PROBABILITY WITHOUT MEASURE. The Historical Context. The Bounded Strong Law of Large Numbers. Kolmogorov's Strong Law of Large Numbers. The Law of the…
Algorithmic Learning in a Random World
- V. Vovk, A. Gammerman, G. Shafer
- Computer Science
- 22 March 2005
Algorithmic Learning in a Random World describes recent theoretical and experimental developments in building computable approximations to Kolmogorov's algorithmic notion of randomness and describes how several important machine learning problems cannot be solved if the only assumption is randomness.
Inductive Confidence Machines for Regression
- H. Papadopoulos, Kostas Proedrou, V. Vovk, A. Gammerman
- Computer ScienceEuropean Conference on Machine Learning
- 19 August 2002
The inductive approach described in this paper may be the only option available when dealing with large data sets and is much faster than the existing transductive techniques.
Conformal Prediction for Reliable Machine Learning: Theory, Adaptations and Applications
- V. Balasubramanian, S. Ho, V. Vovk
- Computer Science
- 13 May 2014
The conformal predictions framework is a recent development in machine learning that can associate a reliable measure of confidence with a prediction in any real-world pattern recognition…
Conditional validity of inductive conformal predictors
- V. Vovk
- MathematicsMachine-mediated learning
- 12 September 2012
Various versions of conditional validity and various ways to achieve them using inductive conformal predictors and their modifications are explored, including a convenient expression of one of the modifications in terms of ROC curves.
Derandomizing Stochastic Prediction Strategies
- V. Vovk
- Computer ScienceCOLT '97
- 1 July 1997
If the stochastic predictor's total loss is at most L with probability at least p then the learner's loss can be bounded by cL + aln for the usual constants c and a and this interpretation is used to revamp known results and obtain new results on tracking the best expert.
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