We study sequential prediction problems in which, at each time instance, the forecaster chooses a vector from a given finite set S ⊆ R. At the same time, the opponent chooses a “loss” vector in R and the forecaster suffers a loss that is the inner product of the two vectors. The goal of the forecaster is to achieve that, in the long run, the accumulated loss is not much larger than that of the ...

Prediction of adversarial course of actions (COA) is critical to many applications including: crime prediction, Unmanned Aerial Vehicle (UAV) threat prediction, and terrorism attack prevention. Researchers have shown that integrating behavior features (or preferences/patterns/modes) into prediction systems, which utilize random process theory and likelihood estimation calculations, can improve ...

We present a general method for using automatic diierentiation to facilitate model sensitivity analysis. Automatic diierentiation techniques augment, in a completely mechanical fashion, an existing code such that it also simultaneously and eeciently computes derivatives. Our method allows the sensitivities of the code's outputs to its parameters and inputs to be determined with minimal human ee...

We investigate a new Follow the Perturbed Leader (FTPL) algorithm for online structured prediction problems. We show a regret bound which is comparable to the state of the art of FTPL algorithms and is comparable with the best possible regret in some cases. To better understand FTPL algorithms for online structured learning, we present a lower bound on the regret for a large and natural class o...

research interests include evolution and learning in games and the economics of technological standardization. Abstract We survey three classes of models from evolutionary game theory which make history independent predictions: stochastic stability, stochastic stability with local interaction, and cheap talk. We argue that of the three, only local interaction models yield credible history indep...

The industry world uses machines and plants that are increasingly powerful and complex. The requirements of high safety, the reduction of the exploitation costs, and the control of the equipment availability give to maintenance a dominating role. The industrialists attach a great importance to the conditional maintenance of the revolving machines that use primarily the vibrations of their rotor...

We discuss basic prediction theory and its impact on classification success evaluation, implications for learning algorithm design, and uses in learning algorithm execution. This tutorial is meant to be a comprehensive compilation of results which are both theoretically rigorous and quantitatively useful. There are two important implications of the results presented here. The first is that comm...

Prediction Markets in Theory and Practice Prediction Markets, sometimes referred to as “information markets,” “idea futures” or “event futures”, are markets where participants trade contracts whose payoffs are tied to a future event, thereby yielding prices that can be interpreted as market-aggregated forecasts. This article summarizes the recent literature on prediction markets, highlighting b...