As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...
Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...
Enzymes with specific functions are becoming increasingly important in industry, medicine and environmental protection. For example, they make it possible to synthesize chemicals in a more ...
Discover how the Modified Dietz Method measures investment returns, factoring in cash flow timing and excluding skewing ...
Machine learning is the ability of a machine to improve its performance based on previous results. Machine learning methods enable computers to learn without being explicitly programmed and have ...
Abstract: To address the issue of positioning accuracy, significant degradation in foot kinematics/micro-inertial navigation system (INS) integrated positioning over long durations, this article ...
Abstract: The coal mine integrated energy system dispatch problem (CMIES-DP) is a constrained multiobjective optimization problem (CMOP) with the characteristics of multiple objectives, ...
Beyond heuristics: take token weighting as optimization, not guesswork. Improving both in-domain accuracy and out-of-domain generalization. Serves as a more effective initialization for subsequent RL.
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