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Found 6 papers, 2 papers with code
$\rm A^2Q$: Aggregation-Aware Quantization for Graph Neural Networks
Through an in-depth analysis of the topology of GNNs, we observe that the topology of the graph leads to significant differences between nodes, and most of the nodes in a graph appear to have a small aggregation value.
Hardware Acceleration of Fully Quantized BERT for Efficient Natural Language Processing
BERT is the most recent Transformer-based model that achieves state-of-the-art performance in various NLP tasks.
Equivalence of Convergence Rates of Posterior Distributions and Bayes Estimators for Functions and Nonparametric Functionals
For a general class of kernels, we establish convergence rates of the posterior measure of the regression function and its derivatives, which are both minimax optimal up to a logarithmic factor for functions in certain classes.
On the Estimation of Derivatives Using Plug-in Kernel Ridge Regression Estimators
We study the problem of estimating the derivatives of a regression function, which has a wide range of applications as a key nonparametric functional of unknown functions.
A System-Level Solution for Low-Power Object Detection
As a case study, we evaluate our object detection system on a real-world surveillance video with input size of 512x512, and it turns out that the system can achieve an inference speed of 18 fps at the cost of 6. 9W (with display) with an mAP of 66. 4 verified on the PASCAL VOC 2012 dataset.
