3.7k citations · 8k across the 129 of their papers we have counts for
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Towards Efficient Scene Understanding via Squeeze Reasoning
Xiangtai Li, Xia Li, Ansheng You +5
Graph-based convolutional model such as non-local block has shown to be effective for strengthening the context modeling ability in convolutional neural networks (CNNs). However, i…
ISTA-NAS: Efficient and Consistent Neural Architecture Search by Sparse Coding
Yibo Yang, Hongyang Li, Shan You +3
Neural architecture search (NAS) aims to produce the optimal sparse solution from a high-dimensional space spanned by all candidate connections. Current gradient-based NAS methods…
Variance Reduced EXTRA and DIGing and Their Optimal Acceleration for Strongly Convex Decentralized Optimization
Huan Li, Zhouchen Lin, Yongchun Fang
We study stochastic decentralized optimization for the problem of training machine learning models with large-scale distributed data. We extend the widely used EXTRA and DIGing met…
Improving Semantic Segmentation via Decoupled Body and Edge Supervision
Xiangtai Li, Xia Li, Li Zhang +5
Existing semantic segmentation approaches either aim to improve the object's inner consistency by modeling the global context, or refine objects detail along their boundaries by mu…
PDO-eConvs: Partial Differential Operator Based Equivariant Convolutions
Zhengyang Shen, Lingshen He, Zhouchen Lin +1
Recent research has shown that incorporating equivariance into neural network architectures is very helpful, and there have been some works investigating the equivariance of networ…
Maximum-and-Concatenation Networks
Xingyu Xie, Hao Kong, Jianlong Wu +3
While successful in many fields, deep neural networks (DNNs) still suffer from some open problems such as bad local minima and unsatisfactory generalization performance. In this wo…