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A K-means Algorithm for Financial Market Risk Forecasting
In today's society, there are problems of high error rate and low precision in financial market risk prediction, which greatly affect the accuracy of financial market risk prediction.
Adapting LLMs for Efficient Context Processing through Soft Prompt Compression
By amalgamating soft prompt compression with sophisticated summarization, SoftPromptComp confronts the dual challenges of managing lengthy contexts and ensuring model scalability.
DAC: Deep Autoencoder-based Clustering, a General Deep Learning Framework of Representation Learning
Clustering performs an essential role in many real world applications, such as market research, pattern recognition, data analysis, and image processing.
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