In this paper we study a dual version of the Ridge Regression procedure which allows the use of kernel functions, as used in Support Vector methods.Expand

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… Expand

Conformal prediction is designed for an on-line setting in which labels are predicted successively, each one being revealed before the next is predicted.Expand

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… Expand

Summary
A radically new approach to statistical modelling, which combines mathematical techniques of Bayesian statistics with the philosophy of the theory of competitive on-line algorithms, has… Expand

Algorithmic Learning in a Random World describes recent theoretical and experimental developments in building computable approximations to Kolmogorov's algorithmic notion of randomness. Based on… Expand

We describe a method for predicting a classification of an object given classifications of the objects in the training set, assuming that the pairs object/classification are generated by an i.d. process from a continuous probability distribution.Expand

Conformal Predictions for Reliable Machine Learning: Theory, Adaptations and Applications captures the basic theory of the framework, demonstrates how to apply it to real-world problems, and presents several adaptations, including active learning, change detection, and anomaly detection.Expand