1.6k citations · 4.8k across the 90 of their papers we have counts for
13 papers · 1 filter
Any-Precision Deep Neural Networks
Haichao Yu, Haoxiang Li, Honghui Shi +2
We present any-precision deep neural networks (DNNs), which are trained with a new method that allows the learned DNNs to be flexible in numerical precision during inference. The s…
Fast Generation for Convolutional Autoregressive Models
Prajit Ramachandran, Tom Le Paine, Pooya Khorrami +6
Convolutional autoregressive models have recently demonstrated state-of-the-art performance on a number of generation tasks. While fast, parallel training methods have been crucial…
Deep Double Sparsity Encoder: Learning to Sparsify Not Only Features But Also Parameters
Zhangyang Wang, Thomas S. Huang
This paper emphasizes the significance to jointly exploit the problem structure and the parameter structure, in the context of deep modeling. As a specific and interesting example,…
Stacked Approximated Regression Machine: A Simple Deep Learning Approach
Zhangyang Wang, Shiyu Chang, Qing Ling +4
With the agreement of my coauthors, I Zhangyang Wang would like to withdraw the manuscript "Stacked Approximated Regression Machine: A Simple Deep Learning Approach". Some experime…
Learning A Deep Encoder for Hashing
Zhangyang Wang, Yingzhen Yang, Shiyu Chang +2
We investigate the -constrained representation which demonstrates robustness to quantization errors, utilizing the tool of deep learning. Based on the Alternating Dire…
Learning with -Graph: -Induced Sparse Subspace Clustering
Yingzhen Yang, Jiashi Feng, Jianchao Yang +1
Sparse subspace clustering methods, such as Sparse Subspace Clustering (SSC) \cite{ElhamifarV13} and -graph \cite{YanW09,ChengYYFH10}, are effective in partitioning the d…