KDD
Member since:
2021-01-05
Last seen:
2021-01-08
User details
Name:
SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
Affiliation:
Association for Computing Machinery (ACM)
Website:
https://www.kdd.org/conferences
About me:
The annual ACM SIGKDD Conference is the premier international forum for data mining researchers and practitioners from academia, industry, and government to share ideas, research results and experiences.
Papertalks of KDD
23/08/2020
Truth discovery against strategic sybil attack in crowdsourcing
Yue Wang, Ke Wang, Chunyan Miao
Keywords Paper
Sybil defense, quality control, crowdsourcing
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0
0
0
13:07
23/08/2020
Attention and memory-augmented networks for dual-view sequential learning
Yong He, Cheng Wang, Nan Li, Zhenyu Zeng
Keywords Paper
intra-attention, medication recommendation, history attention memory, invoice fraud detection, inter-attention, dual-view sequential learning, DRG classification, classification, dynamic external memory
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0
0
0
10:32
23/08/2020
Structural patterns and generative models of real-world hypergraphs
Manh Tuan Do, Se-eun Yoon, Bryan Hooi, Kijung Shin
Keywords Paper
multi-level decomposition, connected component, singular-value distribution, degree distribution, clustering coefficient, diameter, decomposed graph, subset interaction
0
0
0
0
17:39
23/08/2020
GRACE: Generating concise and informative contrastive sample to explain neural network model’s prediction
Thai Le, Suhang Wang, Dongwon Lee
Keywords Paper
contrastive samples, counterfactual samples, neural networks, data generation, interpretability, deep learning, explainability
0
0
0
0
19:07
23/08/2020
How to count triangles, without seeing the whole graph
Suman K. Bera, C. Seshadhri
Keywords Paper
random walks, graph sampling, triangle counting
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0
0
0
19:02
23/08/2020
Incremental lossless graph summarization
Jihoon Ko, Yunbum Kook, Kijung Shin
Keywords Paper
graph summarization, incremental algorithm, graph compression
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0
0
0
18:52
23/08/2020
From online to non-i.i.d. Batch learning
Yufei Tao, Shangqi Lu
Keywords Paper
online-to-batch conversion, learning algorithms, classification
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0
0
0
19:19
23/08/2020
Towards deeper graph neural networks
Meng Liu, Hongyang Gao, Shuiwang Ji
Keywords Paper
graph neural networks, graph representation learning, deep learning
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0
0
0
13:11
23/08/2020
MoFlow: An invertible flow model for generating molecular graphs
Chengxi Zang, Fei Wang
Keywords Paper
graph generative model, de novo drug design, molecular graph generation, molecular graph optimization, deep generative model, graph conditional flow, graph normalizing flow
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0
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0
23:46
