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	<title>multi-class classification &#8211; BIOENGINEER.ORG</title>
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		<title>Evolutionary AI Discovers Leaner Neural Networks by Treating Every Class as Its Own Goal</title>
		<link>https://bioengineer.org/evolutionary-ai-discovers-leaner-neural-networks-by-treating-every-class-as-its-own-goal/</link>
		
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		<pubDate>Mon, 12 Oct 2026 16:12:53 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[AutoML]]></category>
		<category><![CDATA[deep learning]]></category>
		<category><![CDATA[evolutionary algorithms]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<category><![CDATA[many-objective optimization]]></category>
		<category><![CDATA[MOEA/D]]></category>
		<category><![CDATA[multi-class classification]]></category>
		<category><![CDATA[Neural architecture search]]></category>
		<category><![CDATA[Pareto front]]></category>
		<category><![CDATA[pruning]]></category>
		<category><![CDATA[ResNet-18]]></category>
		<category><![CDATA[Transfer Learning]]></category>
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					<description><![CDATA[Researchers have reformulated multi-class classification as a many-objective problem in which each class is a separate goal, using evolutionary neural architecture search and a frozen pre-trained feature extractor to discover Pareto-optimal networks that are far smaller than ResNet-18 benchmarks with minimal accuracy loss.]]></description>
		
		
		
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