Abstract: Real-world software–hardware co-design for AI accelerators must meet strict constraints on accuracy and PPA, making design space exploration both costly and inefficient. In this work, we ...
BONNI optimizes any black box function WITH gradient information. Especially in optimizations with many degree of freedom, gradient-information increases optimization speed. In the image, the ...
The training error decreases with increasing neuron count and plateaus beyond 28 neurons per hidden layer. For the two-hidden-layer network, error stabilization is ...
Abstract: This article proposes a novel constrained multiobjective evolutionary Bayesian optimization algorithm based on decomposition (named CMOEBO/D) for expensive constrained multiobjective ...
SLSQP stands for Sequential Least Squares Programming. It is a numerical optimization algorithm used to solve constrained nonlinear optimization problems. In this project, we aim to optimize objective ...
State Key Laboratory of Tribology in Advanced Equipment, Tsinghua University, Beijing 100084, China State Key Laboratory of Clean and Efficient Turbomachinery Power Equipment, Department of Mechanical ...
High-entropy oxides (HEOs), first proposed in 2015, are a novel class of materials attracting significant attention because of their potential to exhibit unexpected physical properties arising from ...
ABSTRACT: Mathematical optimization is a fundamental aspect of machine learning (ML). An ML task can be conceptualized as optimizing a specific objective using the training dataset to discern patterns ...
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