Department of Materials Science and Processing, -Faculty of Engineering, Osaka University, 2-1 Yamadaoka, Suita 565 JAPAN Application of extreme value stati'iiics to corrosion is rcvieweJ. It is cmpha sized that the concept of corroiiion probability is important for a quanlitalivc evaluatioti Of corrosion failure and its prediction, especially for localized corrosion. Extreme value statistics i...

We study the extreme value distribution of stochastic processes modeled by superstatistics. Classical extreme value theory asserts that (under mild asymptotic independence assumptions) only three possible limit distributions are possible, namely: Gumbel, Fréchet and Weibull distribution. On the other hand, superstatistics contains three important universality classes, namely χ-superstatistics, ...

Extreme value theory deals with the stochastic behavior of the extreme values in a process. For a single process, the behavior of the maxima can be described by the three extreme value distributions–Gumbel, Fréchet and negative Weibull–as suggested by Fisher and Tippett (1928). Kotz and Nadarajah (2000) indicated that the extreme value distributions could be traced back to the work done by Bern...

The novel unseen classes can be formulated as the extreme values of known classes. This inspired the recent works on open-set recognition [32, 31, 28], which however can have no way of naming the novel unseen classes. To solve this problem, we propose the Extreme Value Learning (EVL) formulation to learn the mapping from visual feature to semantic space. To model the margin and coverage distrib...

in many applications, ranking of decision making units (dmus) is a problematic technical task procedure to decision makers in data envelopment analysis (dea), especially when there are extremely efficient dmus. in such cases, many dea models may usually get the same efficiency score for different dmus. hence, there is a growing interest in ranking techniques yet. the purpose of this paper is ra...

We translate in semi-group theory our proof of Varadhan estimates for subelliptic Laplacians which was using the theory of large deviations of Wentzel-Freidlin and the Malliavin Calculus of Bismut type. Key–Words: Large deviations. Subelliptic estimates.

Recognition problems in computer vision often benefit from 5 5 a fusion of different algorithms and/or sensors, with score level fusion be6 6 ing among the most widely used fusion approaches. Score level fusion re7 7 quires the different data to be normalized before combining. Choosing an 8 8 appropriate score normalization technique before fusion is a fundamen9 9 tally difficult problem becaus...