بدائل البحث:
learning algorithm » learning algorithms (توسيع البحث)
using algorithms » pacing algorithms (توسيع البحث), nine algorithms (توسيع البحث), sorting algorithms (توسيع البحث)
element learning » excellent learning (توسيع البحث), student learning (توسيع البحث), agent learning (توسيع البحث)
coding algorithm » cosine algorithm (توسيع البحث), modeling algorithm (توسيع البحث), finding algorithm (توسيع البحث)
learning algorithm » learning algorithms (توسيع البحث)
using algorithms » pacing algorithms (توسيع البحث), nine algorithms (توسيع البحث), sorting algorithms (توسيع البحث)
element learning » excellent learning (توسيع البحث), student learning (توسيع البحث), agent learning (توسيع البحث)
coding algorithm » cosine algorithm (توسيع البحث), modeling algorithm (توسيع البحث), finding algorithm (توسيع البحث)
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Dataset for Fine-Tuning Code Generation Models: Kannada-English Algorithmic Statements and Python Code
منشور في 2025"…<p dir="ltr">This dataset was designed to fine-tune code-generation models for converting algorithmic statements written in Kannada or English into Python code. …"
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Algorithmic experimental parameter design.
منشور في 2024"…Finally, we derive an off-grid sparse model for the reconstructed signal by exploiting sparsity in the null domain and use Bayesian learning to compute the maximum a posteriori probability of the source signal, thus achieving DOA estimation. …"
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Spatial spectrum estimation for three algorithms.
منشور في 2024"…Finally, we derive an off-grid sparse model for the reconstructed signal by exploiting sparsity in the null domain and use Bayesian learning to compute the maximum a posteriori probability of the source signal, thus achieving DOA estimation. …"
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Data and code resources.
منشور في 2025"…This behavior was consistent with a computational process based on the successor representation known as successor features and generalized policy improvement (SF&GPI). Neither model-free perseveration or model-based control using a complete model of the environment could explain choice behavior. …"
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Mitochondrial toxic prediction of marine alga toxins using a predictive model based on feature coupling and ensemble learning algorithms
منشور في 2025"…By comparing 8 machine learning algorithms and using a weighted soft voting method to integrate the two optimal algorithms, we established 108 prediction models and identified the best ensemble learning model MACCS_LK for screening and defining its application domain. …"
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Temporal response patterns determined by Dirichlet Process-based clustering algorithm across amplitudes and stimuli.
منشور في 2024"…<p>The average neuronal activity for each cluster of the Contact <b>(a)</b>, Rough <b>(b)</b> and Smooth stimulus <b>(c)</b> were determined using the Dirichlet Process Mixture Model (DPM) clustering algorithm. …"
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Table 6_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx
منشور في 2025"…These genes had an abundance of antioxidant responsive elements and abscisic acid responsive elements in their promoter region, suggesting their role in stress response. …"
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Table 7_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx
منشور في 2025"…These genes had an abundance of antioxidant responsive elements and abscisic acid responsive elements in their promoter region, suggesting their role in stress response. …"
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Table 3_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx
منشور في 2025"…These genes had an abundance of antioxidant responsive elements and abscisic acid responsive elements in their promoter region, suggesting their role in stress response. …"
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Table 2_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx
منشور في 2025"…These genes had an abundance of antioxidant responsive elements and abscisic acid responsive elements in their promoter region, suggesting their role in stress response. …"