We present a family of margin based online learning algorithms for various prediction tasks. In particular we derive and analyze algorithms for binary and multiclass categorizatio...
In this paper, we consider online prediction from expert advice in a situation where each expert observes its own loss at each time while the loss cannot be disclosed to others fo...
In this work we show how to use efficient online trading algorithms to price the current value of financial instruments, such as an option. We derive both upper and lower bounds f...
On-line boosting is a recent advancement in the field of machine learning that has opened a new spectrum of possibilities in many diverse fields. With respect to a static strong...
Ingrid Visentini, Lauro Snidaro, Gian Luca Foresti
Competitive on-line prediction (also known as universal prediction of individual sequences) is a strand of learning theory avoiding making any stochastic assumptions about the way...