Results 261 to 270 of about 34,598,226 (325)
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IEEE transactions on power electronics, 2020
This article presents an online data-driven diagnosis method for multiple insulated gate bipolar transistors (IGBTs) open-circuit faults and current sensor faults in the three-phase pulsewidth modulation inverter.
Bin Gou +4 more
semanticscholar +1 more source
This article presents an online data-driven diagnosis method for multiple insulated gate bipolar transistors (IGBTs) open-circuit faults and current sensor faults in the three-phase pulsewidth modulation inverter.
Bin Gou +4 more
semanticscholar +1 more source
SIG Bulletin, 1984
[This article is reprinted from the fourth Reports to Decision Makers published by Northwest Regional Educational Laboratory. These reports are produced to provide non-technical people with an accurate overview of certain areas in computer technology and computer education.]
Jim Pollard, Don Holznagel
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[This article is reprinted from the fourth Reports to Decision Makers published by Northwest Regional Educational Laboratory. These reports are produced to provide non-technical people with an accurate overview of certain areas in computer technology and computer education.]
Jim Pollard, Don Holznagel
openaire +1 more source
arXiv.org
Reinforcement learning (RL) has become an effective approach for fine-tuning large language models (LLMs), particularly to enhance their reasoning capabilities.
Yifan Sun +6 more
semanticscholar +1 more source
Reinforcement learning (RL) has become an effective approach for fine-tuning large language models (LLMs), particularly to enhance their reasoning capabilities.
Yifan Sun +6 more
semanticscholar +1 more source
The Importance of Online Data: Understanding Preference Fine-tuning via Coverage
Neural Information Processing SystemsLearning from human preference data has emerged as the dominant paradigm for fine-tuning large language models (LLMs). The two most common families of techniques -- online reinforcement learning (RL) such as Proximal Policy Optimization (PPO) and offline
Yuda Song +4 more
semanticscholar +1 more source
OnlineAugment: Online Data Augmentation with Less Domain Knowledge
European Conference on Computer Vision, 2020Data augmentation is one of the most important tools in training modern deep neural networks. Recently, great advances have been made in searching for optimal augmentation policies in the image classification domain.
Zhiqiang Tang +5 more
semanticscholar +1 more source
IEEE transactions on industrial electronics (1982. Print)
In practical applications, it is time-consuming and laborious to collect sufficient labeled samples for the data-driven fault diagnosis of motor drives. To solve this issue, this article proposes an online data-driven semisupervised diagnosis method for ...
Luhan Jin +4 more
semanticscholar +1 more source
In practical applications, it is time-consuming and laborious to collect sufficient labeled samples for the data-driven fault diagnosis of motor drives. To solve this issue, this article proposes an online data-driven semisupervised diagnosis method for ...
Luhan Jin +4 more
semanticscholar +1 more source
2005
Several approaches for intelligent data analysis are not only available but also tried and tested. Online analytical processing (OLAP) and data mining represent two of the most important approaches. They mainly emphasize different aspects of the data and allow deriving of different kinds of information. So far, these approaches have mainly been used in
Héctor Oscar Nigro +1 more
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Several approaches for intelligent data analysis are not only available but also tried and tested. Online analytical processing (OLAP) and data mining represent two of the most important approaches. They mainly emphasize different aspects of the data and allow deriving of different kinds of information. So far, these approaches have mainly been used in
Héctor Oscar Nigro +1 more
openaire +1 more source
2015
While sexting between young people has become a significant cultural phenomenon, a topic of popular media discussion, and the target of concern from law and policymakers, when it comes to young people themselves our knowledge of their practices and perspectives in relation to sexting is still relatively limited.
Thomas Crofts +3 more
openaire +1 more source
While sexting between young people has become a significant cultural phenomenon, a topic of popular media discussion, and the target of concern from law and policymakers, when it comes to young people themselves our knowledge of their practices and perspectives in relation to sexting is still relatively limited.
Thomas Crofts +3 more
openaire +1 more source
Journal of Science Education and Technology, 2002
Online data collection is becoming an essential and efficient tool for evaluators, researchers, and other educators. This paper touches on elements of the rather short, but eventful history of online data collection. A brief review of the current literature is presented, followed by a list of pros and cons to be considered when stepping into online ...
Neal W. Topp, Bob Pawloski
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Online data collection is becoming an essential and efficient tool for evaluators, researchers, and other educators. This paper touches on elements of the rather short, but eventful history of online data collection. A brief review of the current literature is presented, followed by a list of pros and cons to be considered when stepping into online ...
Neal W. Topp, Bob Pawloski
openaire +1 more source
IEEE Transactions on Information Theory, 2011
We study online learning of linear and kernel-based predictors, when individual examples are corrupted by random noise, and both examples and noise type can be chosen adversarially and change over time. We begin with the setting where some auxiliary information on the noise distribution is provided, and we wish to learn predictors with respect to the ...
N. Cesa-Bianchi +2 more
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We study online learning of linear and kernel-based predictors, when individual examples are corrupted by random noise, and both examples and noise type can be chosen adversarially and change over time. We begin with the setting where some auxiliary information on the noise distribution is provided, and we wish to learn predictors with respect to the ...
N. Cesa-Bianchi +2 more
openaire +1 more source