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Found 6 papers, 1 papers with code
JUMBO: Scalable Multi-task Bayesian Optimization using Offline Data
Such a decomposition can dynamically control the reliability of information derived from the online and offline data and the use of pretrained neural networks permits scalability to large offline datasets.
GACEM: Generalized Autoregressive Cross Entropy Method for Multi-Modal Black Box Constraint Satisfaction
In this work we present a new method of black-box optimization and constraint satisfaction.
Tuning Algorithms and Generators for Efficient Edge Inference
A surge in artificial intelligence and autonomous technologies have increased the demand toward enhanced edge-processing capabilities.
BagNet: Berkeley Analog Generator with Layout Optimizer Boosted with Deep Neural Networks
The discrepancy between post-layout and schematic simulation results continues to widen in analog design due in part to the domination of layout parasitics.
MPDCompress - Matrix Permutation Decomposition Algorithm for Deep Neural Network Compression
Deep neural networks (DNNs) have become the state-of-the-art technique for machine learning tasks in various applications.
Structured Deep Neural Network Pruning via Matrix Pivoting
Deep Neural Networks (DNNs) are the key to the state-of-the-art machine vision, sensor fusion and audio/video signal processing.
