3 papers
cs.LG2020
Recurrence of Optimum for Training Weight and Activation Quantized Networks
Ziang Long, Penghang Yin, Jack Xin
Deep neural networks (DNNs) are quantized for efficient inference on resource-constrained platforms. However, training deep learning models with low-precision weights and activatio…
cs.LG2020
Learning Quantized Neural Nets by Coarse Gradient Method for Non-linear Classification
Ziang Long, Penghang Yin, Jack Xin
Quantized or low-bit neural networks are attractive due to their inference efficiency. However, training deep neural networks with quantized activations involves minimizing a disco…
cs.LG2020
Global Convergence and Geometric Characterization of Slow to Fast Weight Evolution in Neural Network Training for Classifying Linearly Non-Separable Data
Ziang Long, Penghang Yin, Jack Xin
In this paper, we study the dynamics of gradient descent in learning neural networks for classification problems. Unlike in existing works, we consider the linearly non-separable c…