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University of California
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Frequency-band features and a novel MLP architecture boost tracking accuracy by 20% over traditional methods, even in noisy environments.
MResOpt achieves significantly lower high-priority constraint violations in constrained optimization tasks while remaining computationally efficient, revolutionizing how we approach complex optimization problems.
