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 ...
This project implements state-of-the-art deep learning models for financial time series forecasting with a focus on uncertainty quantification. The system provides not just point predictions, but ...
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 ...
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 ...
Graduate School of Science and Technology, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara 630-0192, Japan Graduate School of Science and Technology, Nara Institute of ...
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