activity
20172021
most citedGlobal Sparse Momentum SGD for Pruning Very Deep Neural Networks

125 citations · 409 across the 32 of their papers we have counts for

collaborators

59 papers

cs.CV20212 cited

Joint Channel and Weight Pruning for Model Acceleration on Moblie Devices

Tianli Zhao, Xi Sheryl Zhang, Wentao Zhu +4

For practical deep neural network design on mobile devices, it is essential to consider the constraints incurred by the computational resources and the inference latency in various…

cs.IR2021

Deep Keyphrase Completion

Yu Zhao, Jia Song, Huali Feng +4

Keyphrase provides accurate information of document content that is highly compact, concise, full of meanings, and widely used for discourse comprehension, organization, and text r…

eess.SY20212 cited

Multi-Layer SIS Model with an Infrastructure Network

Philip E. Pare, Axel Janson, Sebin Gracy +3

This paper deals with the spread of diseases over both a population network and an infrastructure network. We develop a layered networked spread model for a susceptible-infected-su…

cs.CV2021

GDP: Stabilized Neural Network Pruning via Gates with Differentiable Polarization

Yi Guo, Huan Yuan, Jianchao Tan +3

Model compression techniques are recently gaining explosive attention for obtaining efficient AI models for various real-time applications. Channel pruning is one important compres…

cs.IR20217 cited

POSO: Personalized Cold Start Modules for Large-scale Recommender Systems

Shangfeng Dai, Haobin Lin, Zhichen Zhao +5

Recommendation for new users, also called user cold start, has been a well-recognized challenge for online recommender systems. Most existing methods view the crux as the lack of i…

physics.chem-ph2021

ChemiRise: a data-driven retrosynthesis engine

Xiangyan Sun, Ke Liu, Yuquan Lin +9

We have developed an end-to-end, retrosynthesis system, named ChemiRise, that can propose complete retrosynthesis routes for organic compounds rapidly and reliably. The system was…