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20202025
most citedSelf-PU: Self Boosted and Calibrated Positive-Unlabeled Training

29 citations · 93 across the 15 of their papers we have counts for

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Showing 2021Show all

5 papers · 1 filter

cs.LG2021★ 6 cited

You are caught stealing my winning lottery ticket! Making a lottery ticket claim its ownership

Xuxi Chen, Tianlong Chen, Zhenyu Zhang +1

Despite tremendous success in many application scenarios, the training and inference costs of using deep learning are also rapidly increasing over time. The lottery ticket hypothes…

cs.LG2021★ 10 cited

Sanity Checks for Lottery Tickets: Does Your Winning Ticket Really Win the Jackpot?

Xiaolong Ma, Geng Yuan, Xuan Shen +8

There have been long-standing controversies and inconsistencies over the experiment setup and criteria for identifying the "winning ticket" in literature. To reconcile such, we rev…

cs.LG2021★ 7 cited

Efficient Lottery Ticket Finding: Less Data is More

Zhenyu Zhang, Xuxi Chen, Tianlong Chen +1

The lottery ticket hypothesis (LTH) reveals the existence of winning tickets (sparse but critical subnetworks) for dense networks, that can be trained in isolation from random init…

cs.LG2021★ 5 cited

GANs Can Play Lottery Tickets Too

Xuxi Chen, Zhenyu Zhang, Yongduo Sui +1

Deep generative adversarial networks (GANs) have gained growing popularity in numerous scenarios, while usually suffer from high parameter complexities for resource-constrained rea…

cs.LG2021★ 27 cited

A Unified Lottery Ticket Hypothesis for Graph Neural Networks

Tianlong Chen, Yongduo Sui, Xuxi Chen +2

With graphs rapidly growing in size and deeper graph neural networks (GNNs) emerging, the training and inference of GNNs become increasingly expensive. Existing network weight prun…