The Extreme Value Machine
نویسندگان
چکیده
منابع مشابه
The Extreme Value Machine – Supplemental Material
For brevity, we adopt array notation. The function takes four arguments (cf. line 1): X and y correspond to all training data and labels respectively, τ is the tailsize, and ς is the coverage threshold. The training function then iterates through every class Cl ∈ C (line 2), fitting a vector of Ψ-models (Ψl) for that class (line 3). The fitting function is presented in Alg. 2 and takes four arg...
متن کاملEnsembles of extreme learning machine networks for value prediction
Value prediction is an important subproblem of several reinforcement learning (RL) algorithms. In a previous work, it has been shown that the combination of least-squares temporal-difference learning with ELM (extreme learning machine) networks is a powerful method for value prediction in continuous-state problems. This work proposes the use of ensembles to improve the approximation capabilitie...
متن کاملhigh volatility, thick tails and extreme value theory in value at risk estimation: the case of liability insurance in iran insurance company
در این بررسی ابتدا به بررسی ماهیت توزیع خسارات پرداخته میشود و از روش نظریه مقادیر نهایی برای بدست آوردن برآورد ارزش در معرض خطر برای خسارات روزانه بیمه مسئولیت شرکت بیمه ایران استفاده میشود. سپس کارایی نظریه مقدار نهایی در برآورد ارزش در معرض خطر با کارایی سایر روشهای واریانس ، کواریانس و روش شبیه سازی تاریخی مورد مقایسه قرار میگیرد. نتایج این بررسی نشان میدهند که توزیع ،garch شناخته شده مدل...
15 صفحه اولExtreme Learning Machine
Slow speed of feedforward neural networks has been hampering their growth for past decades. Unlike traditional algorithms extreme learning machine (ELM) [5][6] for single hidden layer feedforward network (SLFN) chooses input weight and hidden biases randomly and determines the output weight through linear algebraic manipulations. We propose ELM as an auto associative neural network (AANN) and i...
متن کاملExtreme Value Theory
Extreme Value Theory is the branch of statistics that is used to model extreme events. The topic is of interest to meteorologists because much of the recent literature on climate change has focussed on the possibility that extreme events (very high or low temperatures, high precipitation events, droughts, hurricanes etc.) may be changing in parallel with global warming. As a specific example, t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Pattern Analysis and Machine Intelligence
سال: 2018
ISSN: 0162-8828,2160-9292
DOI: 10.1109/tpami.2017.2707495