PSO-lite
PulseAugur coverage of PSO-lite — every cluster mentioning PSO-lite across labs, papers, and developer communities, ranked by signal.
3 day(s) with sentiment data
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New MMAO-Cls method optimizes classification models with compact feature selection
Researchers have developed MMAO-Cls, a novel approach that adapts the Metabolic Multi-Agent Optimizer (MMAO) for classification model selection. This method jointly encodes feature masks and classifier hyperparameters, …
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New MMAO-Cls method optimizes feature selection and classifier tuning
Researchers have developed MMAO-Cls, a novel approach that utilizes the Metabolic Multi-Agent Optimizer (MMAO) for selecting features and tuning classifiers in machine learning models. This method jointly encodes featur…
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MMAO framework shows strong performance in large-scale empirical evaluation
A new paper evaluates the Metabolic Multi-Agent Optimizer (MMAO) framework, focusing on its resource-allocation principles under strict budget controls. The study employed a large-scale empirical protocol across eight C…
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Metabolic Multi-Agent Optimizer (MMAO) framework validated on benchmarks
A new paper evaluates the Metabolic Multi-Agent Optimizer (MMAO) framework using a stricter empirical protocol. The study tested MMAO's resource-allocation principle on continuous and discrete benchmarks, including CEC2…
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New AI frameworks tackle optimization problems with multi-agent refinement · 4 sources tracked
Researchers have introduced OptiAgent, a multi-agent framework designed to translate natural language descriptions of Operations Research problems into solver-ready mathematical formulations and executable code. This sy…