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20192025
most citedAccelerating Monte Carlo Bayesian Inference via Approximating Predictive Uncertainty over Simplex

9 citations · 18 across the 17 of their papers we have counts for

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Showing 2020Show all

2 papers · 1 filter

cs.CV2020

Direct Quantization for Training Highly Accurate Low Bit-width Deep Neural Networks

Tuan Hoang, Thanh-Toan Do, Tam V. Nguyen +1

This paper proposes two novel techniques to train deep convolutional neural networks with low bit-width weights and activations. First, to obtain low bit-width weights, most existi…

cs.LG2020★ 3 cited

Improve Generalization and Robustness of Neural Networks via Weight Scale Shifting Invariant Regularizations

Ziquan Liu, Yufei Cui, Antoni B. Chan

Using weight decay to penalize the L2 norms of weights in neural networks has been a standard training practice to regularize the complexity of networks. In this paper, we show tha…