Forecasting, a fundamental task in machine learning, involves predicting future values of a time series based on its historical behavior. This paper introduces a novel Hierarchical Patch Based ...
Abstract: Fuzzy mathematical theory is widely used, fuzzy optimization is a branch of fuzzy mathematical theory, the significant application area is artificial intelligence in computer science, ...
Introduction: We present Quantum Adaptive Search (QAGS), a hybrid quantum-classical algorithm for global optimization of multivariate functions. The method employs an adaptive mechanism that ...
Introduction: The increasing emphasis on sustainable finance policies has necessitated the development of advanced mathematical models to optimize bank investment portfolios and debt structures. While ...
ABSTRACT: Given that energy costs are a significant component of overall processing costs in mineral plants, reducing these costs through process optimization or technology adoption enhances the ...
Aligning large language models (LLMs) with human preferences is an essential task in artificial intelligence research. However, current reinforcement learning (RL) methods face notable challenges.
Group Relative Policy Optimization (GRPO) is a novel reinforcement learning method introduced in the DeepSeekMath paper earlier this year. GRPO builds upon the Proximal Policy Optimization (PPO) ...
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