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Found 4 papers, 1 papers with code
Tiny Classifier Circuits: Evolving Accelerators for Tabular Data
This paper proposes a methodology for automatically generating predictor circuits for classification of tabular data with comparable prediction performance to conventional ML techniques while using substantially fewer hardware resources and power.
QNNVerifier: A Tool for Verifying Neural Networks using SMT-Based Model Checking
QNNVerifier is the first open-source tool for verifying implementations of neural networks that takes into account the finite word-length (i. e. quantization) of their operands.
Energy Predictive Models for Convolutional Neural Networks on Mobile Platforms
To address this issue, we provide a comprehensive analysis of building regression-based predictive models for deep learning on mobile devices, based on empirical measurements gathered from the SyNERGY framework. Our predictive modelling strategy is based on two types of predictive models used in the literature:individual layers and layer-type.
To Ensemble or Not Ensemble: When does End-To-End Training Fail?
An interesting question is whether this trend will continue-are there any clear failure cases for E2E training?
