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20092023
most citedLink prediction in complex networks: a local na\"ıve Bayes model

203 citations · 267 across the 21 of their papers we have counts for

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Showing 2022Show all

8 papers · 1 filter

cs.CV2022

Minimum Latency Deep Online Video Stabilization

Zhuofan Zhang, Zhen Liu, Ping Tan +2

We present a novel camera path optimization framework for the task of online video stabilization. Typically, a stabilization pipeline consists of three steps: motion estimating, pa…

cs.LG2022★ 3 cited

BESS: Balanced Entity Sampling and Sharing for Large-Scale Knowledge Graph Completion

Alberto Cattaneo, Daniel Justus, Harry Mellor +7

We present the award-winning submission to the WikiKG90Mv2 track of OGB-LSC@NeurIPS 2022. The task is link-prediction on the large-scale knowledge graph WikiKG90Mv2, consisting of…

cs.IR2022

SML:Enhance the Network Smoothness with Skip Meta Logit for CTR Prediction

Wenlong Deng, Lang Lang, Zhen Liu +1

In light of the smoothness property brought by skip connections in ResNet, this paper proposed the Skip Logit to introduce the skip connection mechanism that fits arbitrary DNN dim…

physics.optics2022★ 6 cited

Enhanced Current Density and Asymmetry of Metal-Insulator-Metal Diodes Based on the Self-Assembly of Pt Nanoparticles for Optical Rectennas

Zhen Liu, Shunsuke Abe, Makoto Shimizu +1

Optical rectennas consist of nano-antennas and nano-scale rectifying diodes, providing extensive prospects for thermal radiation energy harvesting applications. To achieve this, hi…

cs.CV2022★ 1 cited

Ghost-free High Dynamic Range Imaging with Context-aware Transformer

Zhen Liu, Yinglong Wang, Bing Zeng +1

High dynamic range (HDR) deghosting algorithms aim to generate ghost-free HDR images with realistic details. Restricted by the locality of the receptive field, existing CNN-based m…

cs.CR2022★ 1 cited

MUDGUARD: Taming Malicious Majorities in Federated Learning using Privacy-Preserving Byzantine-Robust Clustering

Rui Wang, Xingkai Wang, Huanhuan Chen +4

Byzantine-robust Federated Learning (FL) aims to counter malicious clients and train an accurate global model while maintaining an extremely low attack success rate. Most existing…