From the 1 of 1.2k papers with an AI index.
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- Peking UniversityCN334 papers
- Tsinghua UniversityCN199 papers
- Institute of High Energy PhysicsCN194 papers
- Joint Institute for Nuclear ResearchRU188 papers
- Carnegie Mellon UniversityUS187 papers
- Istituto Nazionale di Fisica Nucleare, Laboratori Nazionali di FrascatiIT184 papers
- Indian Institute of Technology MadrasIN180 papers
- Chinese Academy of SciencesCN164 papers
- University of MinnesotaUS163 papers
- University of Science and Technology of ChinaCN159 papers
- University of Chinese Academy of SciencesCN158 papers
- Seoul National UniversityKR146 papers
46 papers · 1 filter
A Data-driven Region Generation Framework for Spatiotemporal Transportation Service Management
Liyue Chen, Jiangyi Fang, Zhe Yu +3
MAUP (modifiable areal unit problem) is a fundamental problem for spatial data management and analysis. As an instantiation of MAUP in online transportation platforms, region gener…
Interpretability is a Kind of Safety: An Interpreter-based Ensemble for Adversary Defense
Jingyuan Wang, Yufan Wu, Mingxuan Li +3
While having achieved great success in rich real-life applications, deep neural network (DNN) models have long been criticized for their vulnerability to adversarial attacks. Treme…
Hyperbolic Geometric Graph Representation Learning for Hierarchy-imbalance Node Classification
Xingcheng Fu, Yuecen Wei, Qingyun Sun +4
Learning unbiased node representations for imbalanced samples in the graph has become a more remarkable and important topic. For the graph, a significant challenge is that the topo…
Automated Federated Learning in Mobile Edge Networks -- Fast Adaptation and Convergence
Chaoqun You, Kun Guo, Gang Feng +2
Federated Learning (FL) can be used in mobile edge networks to train machine learning models in a distributed manner. Recently, FL has been interpreted within a Model-Agnostic Meta…
SE-GSL: A General and Effective Graph Structure Learning Framework through Structural Entropy Optimization
Dongcheng Zou, Hao Peng, Xiang Huang +5
Graph Neural Networks (GNNs) are de facto solutions to structural data learning. However, it is susceptible to low-quality and unreliable structure, which has been a norm rather th…
FedACK: Federated Adversarial Contrastive Knowledge Distillation for Cross-Lingual and Cross-Model Social Bot Detection
Yingguang Yang, Renyu Yang, Hao Peng +4
Social bot detection is of paramount importance to the resilience and security of online social platforms. The state-of-the-art detection models are siloed and have largely overloo…