Tracking a Small Set of Experts by Mixing Past Posteriors

Freezing and Sleeping: Tracking Experts that Learn by Evolving Past Posteriors

A problem posed by Freund is how to efficiently track a small pool of experts out of a much larger set. This problem was solved when Bousquet and Warmuth introduced their mixing past posteriors (MPP) algorithm in 2001. In Freund’s problem the experts would normally be considered black boxes. However, in this paper we re-examine Freund’s problem in case the experts have internal structure that e...

Tra king a Small Set of Expertsby Mixing Past Posteriors ?

Online Aggregation of Unbounded Signed Losses Using Shifting Experts

For the decision theoretic online (DTOL) setting, we consider methods to construct algorithms that suffer loss not much more than of any sequence of experts distributed along a time interval (shifting experts setting). We present a modified version of the method of Mixing Past Posteriors which uses as basic algorithm AdaHedge with adaptive learning rate. Due to this, we combine the advantages o...

Long-Term Sequential Prediction Using Expert Advice

For the prediction with expert advice setting, we consider methods to construct forecasting algorithms that suffer loss not much more than any of experts in the pool. In contrast to the standard approach, we investigate the case of long-term interval forecasting of time series, that is, each expert issues a sequence of forecasts for a time interval ahead and the master algorithm combines these ...

Quaternary tracking of the Basin changes (Case Study: Ghezel Ozan)

The Ghezel Ozan basin in an area of 50000 KM2 is in the northwest of Iran. Recognition of variables like captivity and deviation of rivers, erosion and compact surfaces, the affects of old lakes by the reflected affects on 1:50000 scaled topographic maps of the region, are some of the points which is tried to find out the changes of Quaternary of the basin. Although Ghezel Ozan basin is ended t...