Data and code resources. by Sam Hall-McMaster (10343795)

Subjects:

Present an algorithm to prove P = NP by Sang-un Lee (22242148)

“…<p dir="ltr">Aiming to prove the P vs. NP problem, a long-standing challenge in computer science, we present a novel deterministic algorithm that solves the Hamiltonian path problem, a representative NP-complete problem, in polynomial time. …”

Present an algorithm to prove P = NP by Sang-un Lee (22242910)

“…<p dir="ltr">Aiming to prove the P vs. NP problem, a long-standing challenge in computer science, we present a novel deterministic algorithm that solves the Hamiltonian path problem, a representative NP-complete problem, in polynomial time. …”

Present an algorithm to prove P = NP by Sang-un Lee (22242055)

“…<p dir="ltr">Aiming to prove the P vs. NP problem, a long-standing challenge in computer science, we present a novel deterministic algorithm that solves the Hamiltonian path problem, a representative NP-complete problem, in polynomial time. …”

Present an algorithm to prove P = NP by Sang-un Lee (22239061)

Notations and definitions used in the algorithm. by Nazym Alimbekova (22766158)

Dataset for Fine-Tuning Code Generation Models: Kannada-English Algorithmic Statements and Python Code by Goutami Sooda (20714729)

The genome coding scheme. by Wenbing Shi (5806160)

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Comparison of Uniform Manifold Approximation and Projection (UMAP)-based and feature-based spike sorting on synthetic data. by Daniel Suárez-Barrera (22676654)

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Ablation experiment for the micro-localization algorithm model. by Zhongjian Xie (4633099)

Ablation experiment for the macro-detection algorithm model. by Zhongjian Xie (4633099)

Identification of CRG based on WGCNA algorithm. by Lin Feng (84785)

Algorithm flow based on CL-EPIDTN. by Fang Yang (123514)

Dynamic window based median filtering algorithm. by Li Yuan (102305)

“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. …”

Curve of data size vs. running time. by Qingnan Ji (22662198)

“…The algorithm dynamically adjusts weight coefficients based on the importance scores of each modality, while also incorporating a cross-modal correlation matrix as a constraint to improve the robustness of the matching process. …”

Algorithm parameter settings employed in the experiments on simulated data. by Liyan Sun (760586)

The parameter setting of the evolutionary neural network. by Wenbing Shi (5806160)

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The errors of the predictions based on different algorithm methods. by Zhang Wei (317854)

Performance profile of the four algorithms based on CPU time. by Sulaiman M. Ibrahim (20614376)

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Performance profile of the four algorithms based on number of iteration. by Sulaiman M. Ibrahim (20614376)

Subjects: