نتایج جستجو برای: online learning algorithm

تعداد نتایج: 1456670  

A. Khatibi Bardsiri F. Parandeh Motlagh

The internet and its various services have made users to easily communicate with each other. Internet benefits including online business and e-commerce. E-commerce has boosted online sales and online auction types. Despite their many uses and benefits, the internet and their services have various challenges, such as information theft, which challenges the use of these services. Information thef...

2015
Alina Beygelzimer Elad Hazan Satyen Kale Haipeng Luo

We extend the theory of boosting for regression problems to the online learning setting. Generalizing from the batch setting for boosting, the notion of a weak learning algorithm is modeled as an online learning algorithm with linear loss functions that competes with a base class of regression functions, while a strong learning algorithm is an online learning algorithm with smooth convex loss f...

In this paper an adaptive PID controller for Wind Energy Conversion Systems (WECS) has been developed. Theadaptation technique applied to this controller is based on Reinforcement Learning (RL) theory. Nonlinearcharacteristics of wind variations as plant input, wind turbine structure and generator operational behaviordemand for high quality adaptive controller to ensure both robust stability an...

Introduction: With the sudden shift of face-to-face education to e-learning during the COVID-19 pandemic, awareness of learnerschr('39') readiness for online learning and its impact on studentschr('39') psychological distress related to e-learning is important for teachers, counselors, and educational planners. Therefore, the present study was conducted to investigate the correlation between on...

2006
Lean Yu Shouyang Wang Kin Keung Lai

In this study, an online learning algorithm for feedforward neural networks (FNN) based on the optimized learning rate and adaptive forgetting factor is proposed for online financial time series prediction. The new learning algorithm is developed for online predictions in terms of the gradient descent technique, and can speed up the FNN learning process substantially relative to the standard FN...

2007
Yiming Ying Massimiliano Pontil

This paper considers the least-square online gradient descent algorithm in a reproducing kernel Hilbert space (RKHS) without an explicit regularization term. We present a novel capacity independent approach to derive error bounds and convergence results for this algorithm. The essential element in our analysis is the interplay between the generalization error and a weighted cumulative error whi...

Journal: :international journal of information science and management 0
s. rezaei sharifabadi ph.d., alzahra university, tehran

digital libraries offer opportunities for e-learning that are not possible in their physical counterparts. digital libraries complement other learning environments, such as those provided in distance education and courses offered online. like e-learning environments, they provide flexibility of time and place. digital libraries have the potential to offer unprecedented resources to support e-le...

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه صنعتی خواجه نصیرالدین طوسی - دانشکده برق و کامپیوتر 1391

in the area of automotive engineering there is a tendency to more electrification of power train. in this work control of an induction machine for the application of electric vehicle is investigated. through the changing operating point of the machine, adapting the rotor magnetization current seems to be useful to increase the machines efficiency. in the literature there are many approaches wh...

2008
Ofer Dekel

We present cutoff averaging, a technique for converting any conservative online learning algorithm into a batch learning algorithm. Most online-to-batch conversion techniques work well with certain types of online learning algorithms and not with others, whereas cutoff averaging explicitly tries to adapt to the characteristics of the online algorithm being converted. An attractive property of o...

2008

We present cutoff averaging, a technique for converting any conservative online learning algorithm into a batch learning algorithm. Most online-to-batch conversion techniques work well with certain types of online learning algorithms and not with others, whereas cutoff averaging explicitly tries to adapt to the characteristics of the online algorithm being converted. An attractive property of o...

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