10 citations · 42 across the 16 of their papers we have counts for
9 papers · 1 filter
Weight Normalization based Quantization for Deep Neural Network Compression
Wen-Pu Cai, Wu-Jun Li
With the development of deep neural networks, the size of network models becomes larger and larger. Model compression has become an urgent need for deploying these network models t…
Clustered Reinforcement Learning
Xiao Ma, Shen-Yi Zhao, Wu-Jun Li
Exploration strategy design is one of the challenging problems in reinforcement learning~(RL), especially when the environment contains a large state space or sparse rewards. Durin…
ADASS: Adaptive Sample Selection for Training Acceleration
Shen-Yi Zhao, Hao Gao, Wu-Jun Li
Stochastic gradient decent~(SGD) and its variants, including some accelerated variants, have become popular for training in machine learning. However, in all existing SGD and its v…
On the Convergence of Memory-Based Distributed SGD
Shen-Yi Zhao, Hao Gao, Wu-Jun Li
Distributed stochastic gradient descent~(DSGD) has been widely used for optimizing large-scale machine learning models, including both convex and non-convex models. With the rapid…
Deep Multi-Index Hashing for Person Re-Identification
Ming-Wei Li, Qing-Yuan Jiang, Wu-Jun Li
Traditional person re-identification (ReID) methods typically represent person images as real-valued features, which makes ReID inefficient when the gallery set is extremely large.…
Gated Group Self-Attention for Answer Selection
Dong Xu, Jianhui Ji, Haikuan Huang +2
Answer selection (answer ranking) is one of the key steps in many kinds of question answering (QA) applications, where deep models have achieved state-of-the-art performance. Among…