204,674 results for machine learning
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Journal Article Full text
Machine learning for filter pollution control
…Subsequent considerations focuses on the test-rig measurements. The machine learning algorithm was trained successfully to detect anomalies of the filter behavior. Finally, the change intervals of the filter may be adapted to the real degree of pollution without the requirement for visual…
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Machine learning depinning of dislocation pileups
We study a one-dimensional model of a dislocation pileup driven by an external stress and interacting with random quenched disorder, focusing on the predictability of the plastic deformation process. Upon quasistatically ramping up the externally applied stress from zero, the system responds by…
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Journal Article
Integrating Machine Learning with Human Knowledge
Summary: Machine learning has been heavily researched and widely used in many disciplines. However, achieving high accuracy requires a large amount of data that is sometimes difficult, expensive, or impractical to obtain. Integrating human knowledge into machine learning can significantly reduce…
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Journal Article Full text
MLitB: machine learning in the browser
With few exceptions, the field of Machine Learning (ML) research has largely ignored the browser as a computational engine. Beyond an educational resource for ML, the browser has vast potential to not only improve the state-of-the-art in ML research, but also, inexpensively and on a massive scale…
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Diversity in sociotechnical machine learning systems
There has been a surge of recent interest in sociocultural diversity in machine learning research. Currently, however, there is a gap between discussions of measures and benefits of diversity in machine learning, on the one hand, and the broader research on the underlying concepts of diversity and…
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Probabilistic Machine Learning Using Bayesian Inference
Machine Learning is a branch of AI (Artificial Intelligence) which expands on the idea of a computational system extending its knowledge about set methodical behaviors from the data that is fed to it to essentially develop analytical skills that can help in identifying patterns and making decisions…
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Phishing attack detection using Machine Learning
…against phishing approaches. This paper examines the association of Machine Literacy routes in identifying phishing assaults and records their advantages and drawbacks. There are countless Machine Learning calculations that have been dug to proclaim the relevant decision that act as against…
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Journal Article
Testing swampland conjectures with machine learning
Abstract We consider Type IIB compactifications on an isotropic torus $$T^6$$ T6 threaded by geometric and non geometric fluxes. For this particular setup we apply supervised machine learning techniques, namely an artificial neural network coupled to a genetic algorithm, in order to obtain more…
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Machine learning on normalized protein sequences
Abstract Background Machine learning techniques have been widely applied to biological sequences, e.g. to predict drug resistance in HIV-1 from sequences of drug target proteins and protein functional classes. As deletions and insertions are frequent in biological sequences, a major limitation of…
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Journal Article Full text
Machine Learning in Stock Price Forecast
This paper analyzed and compared the forecast effect of three machine learning algorithms (multiple linear regression, random forest and LSTM network) in stock price forecast using the closing price data of NASDAQ ETF and data of statistical factors. The test results show that the prediction effect…
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TOML Transistor Operations for Machine Learning
The escalating energy consumption of machine learning systems demands accurate, physics-grounded efficiency measurement beyond conventional proxies like FLOPs and MACs, which fail to capture non-linear operations and memory access costs. While recent work established transistor operations (TOs) as…
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Journal Article
Forecasting sports outcomes through machine learning
IntroductionMachine learning has increasingly been applied to forecast sports outcomes, assess player performance, estimate injury risk, and model in-game events, yet the reported evidence remains fragmented across sports and validation practices.MethodsTo address this fragmentation, this…
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Machine learning of the prime distribution.
…posit that the Erdős-Kac law would very unlikely be discovered by current machine learning techniques. Numerical experiments that we perform corroborate our theoretical findings.
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Journal Article
DDoS Attack Detection with Machine Learning
…of DDoS detection. In this paper, a DDoS detection method utilizing machine learning is proposed. There are three type of supervised machine learning classification methods which are K-Nearest Neighbor, Multilayer Perceptron and Random Forest, are applied in the proposed work to assess the accuracy…
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Journal Article
MACHINE LEARNING METHODS FOR PHISHING ATTACKS
…with the development of technology, phishing methods have also evolved. Machine learning has been effectively used to identify and avoid phishing. The reason of this consider is to survey machine learning methods and the comes about of previous thinks about on the avoidance of phishing attacks. As…
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Journal Article
HARNESSING GPU POWER FOR MACHINE LEARNING
In the rapidly evolving landscape of data science and machine learning, the need for high-speed, efficient data processing is more critical than ever. This article delves into the pivotal role of graphics processing units (GPUs) in transforming the realm of data analytics and machine learning…
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Journal Article
Machine learning applications in drug development
Due to the huge amount of biological and medical data available today, along with well-established machine learning algorithms, the design of largely automated drug development pipelines can now be envisioned. These pipelines may guide, or speed up, drug discovery; provide a better understanding of…
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Journal Article
Smart Archives: A Machine Learning Approach
…and poor adaptation to heterogeneous formats. While the avenue that machine learning (ML) presents is highly promising for transformation, its exploration within the domain of archival science remains limited, with specific emphasis on multimodal data. This study outlines a hybrid ML framework to…
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Journal Article Full text
Organ Segmentation with Machine Learning Models
Accurate segmentation of abdominal organs in Computed Tomography (CT) underpins radiotherapy planning, surgical planning, and disease monitoring. Existing benchmarks rank architectures by a single aggregate Dice score, without per-organ statistical testing or boundary-sensitive metrics, even though…
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